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1. Fuzzy Logic - Wikipedia, The Free Encyclopedia Fuzzy logic is derived from Fuzzy set theory dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic. http://en.wikipedia.org/wiki/Fuzzy_logic

var wgNotice = ""; var wgNoticeLocal = ""; var wgNoticeLang = "en"; var wgNoticeProject = "wikipedia"; Fuzzy logic From Wikipedia, the free encyclopedia Jump to: navigation search For the Super Furry Animals album, see Fuzzy Logic (album) Fuzzy logic is derived from fuzzy set theory dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic . It can be thought of as the application side of fuzzy set theory dealing with well thought out real world expert values for a complex problem (Klir 1997). Degrees of truth are often confused with probabilities . However, they are conceptually distinct; fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition. For example, if a 100-ml glass contains 30 ml of water, then, for two fuzzy sets, Empty and Full, one might define the glass as being 0.7 empty and 0.3 full. Note that the concept of emptiness would be subjective and thus would depend on the observer or designer. Another designer might equally well design a set membership function where the glass would be considered full for all values down to 50 ml. A probabilistic setting would first define a scalar variable for the fullness of the glass, and second, conditional distributions describing the probability that someone would call the glass full given a specific fullness level. Note that the conditioning can be achieved by having a specific observer that randomly selects the label for the glass, a distribution over deterministic observers, or both. While fuzzy logic avoids talking about randomness in this context, this simplification at the same time obscures what is exactly meant by the statement the 'glass is 0.3 full'.

2. Fuzzy Logic Tutorial - An Introduction Fuzzy logic Tutorial. PART I Introduction to Fuzzy logic INTRODUCTION WHERE DID Fuzzy logic COME FROM? WHAT IS Fuzzy logic? http://www.seattlerobotics.org/encoder/mar98/fuz/flindex.html

SRS Home Front Page Monthly Issue Index Search WWW Search seattlerobotics.org Fuzzy Logic Tutorial PART I - Introduction to Fuzzy Logic INTRODUCTION WHERE DID FUZZY LOGIC COME FROM? WHAT IS FUZZY LOGIC? ... Author Information

3. Fuzzy Logic Archive The Net s Original Fuzzy logic Archive Since 1994. http://www.austinlinks.com/Fuzzy/

The Net's Original Fuzzy Logic Archive - Since 1994 Basics Beverly's Fuzzy Logic Bookstore Brief Course in Fuzzy Logic comp.ai.fuzzy Frequently Asked Questions UseNet Eric Horstkotte on Fuzzy Logic Part 1 - Overview Part 2 - Fuzzy Expert Systems Part 3 - Fuzzy Environmental Control Fuzzy for Beginners ... Fuzzy Logic in Consumer Products Take the Fuzzy Shower Challenge Fuzzy Systems - A Tutorial Fuzzy Logic Development Environment Lotfi Zadeh - Founder of Fuzzy Logic info at austinlinks.com SiteTerrific Web Solutions

4. FAQ: Fuzzy Logic And Fuzzy Expert Systems 1/1 [Monthly Posting] 7 What are Fuzzy numbers and Fuzzy arithmetic? 8 Isn t Fuzzy logic an inherent contradiction? Why would anyone want to fuzzify logic? http://www.cs.cmu.edu/Groups/AI/html/faqs/ai/fuzzy/part1/faq.html

Introduction [1] What is the purpose of this newsgroup? [2] What is fuzzy logic? [3] Where is fuzzy logic used? Introduction [1] What is the purpose of this newsgroup? [2] What is fuzzy logic? [3] Where is fuzzy logic used? ... [24] Where to send calls for papers (cfp) and calls for participation

5. Fuzzy Logic The principal constituents of soft computing (SC) are Fuzzy logic (FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter http://www.abo.fi/~rfuller/fuzs.html

Fuzzy Sets and Systems Lotfi A. Zadeh , The founder of fuzzy logic comp.ai.fuzzy New fuzzy archive by thread. Fuzzy Logic Tools and Companies. General sources of fuzzy information. Maintained by Bob John. World Federation on Soft Computing Artificial Intelligence-related Frequently Asked Questions Professional Organizations and Networks International Fuzzy Systems Association (IFSA) IFSA is a worldwide organization dedicated to the support and development of the theory of fuzzy sets and systems and related areas and their applications, publishes the International Journal of Fuzzy Sets and Systems, holds International conferences, establishes chapters and sponsors other activities. Berkeley Initiative in Soft Computing (BISC) BISC Program is the world-leading center for basic and applied research in soft computing. The principal constituents of soft computing (SC) are fuzzy logic (FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter subsuming belief networks, evolutionary computing including DNA computing, chaos theory and parts of learning theory. North American Fuzzy Information Processing Society (NAFIPS) As the premier fuzzy society in North America established in 1981, our purpose is to help guide and encourage the development of fuzzy sets and related technologies for the benefit of mankind.

6. The MathWorks - Fuzzy Logic Toolbox - Design And Simulate Fuzzy Logic Systems The Fuzzy logic Toolbox extends the MATLAB technical computing environment with tools for the design of systems based on Fuzzy logic. http://www.mathworks.com/products/fuzzylogic/

var host_pre = "http://www"; Home Select Country Contact Us Store Search Create Account Log In Industries Academia ... Documentation Other Resources Technical Literature Related Books Fuzzy Logic Toolbox 2.2.6 Design and simulate fuzzy logic systems The Fuzzy Logic Toolbox extends the MATLAB technical computing environment with tools for designing systems based on fuzzy logic. Graphical user interfaces (GUIs) guide you through the steps of fuzzy inference system design. Functions are provided for many common fuzzy logic methods, including fuzzy clustering and adaptive neurofuzzy learning. Introduction and Key Features Working with the Fuzzy Logic Toolbox Building a Fuzzy Inference System Modeling Using Fuzzy Logic ... View data sheet Press Release: The MathWorks Opens Office in Beijing, China Featured Demo:  Demos available at upcoming trade shows Contact sales Free technical kit Trial software ... RSS

7. Fuzzy Logic (Stanford Encyclopedia Of Philosophy) The term Fuzzy logic emerged in the development of the theory of Fuzzy sets by Lotfi Zadeh (1965). A Fuzzy subset A of a (crisp) set X is characterized by http://plato.stanford.edu/entries/logic-fuzzy/

Cite this entry Search the SEP Advanced Search Tools ... Please Read How You Can Help Keep the Encyclopedia Free Fuzzy Logic First published Tue Sep 3, 2002; substantive revision Sun Jul 23, 2006 The term "fuzzy logic" emerged in the development of the theory of fuzzy sets by Lotfi Zadeh ( ). A fuzzy subset A of a (crisp) set X is characterized by assigning to each element x of X the degree of membership of x in A (e.g., X is a group of people, A the fuzzy set of old people in X ). Now if X is a set of propositions then its elements may be assigned their degree of truth intermediate connectives truth functions different from probability theory since the latter is not truth-functional (the probability of conjunction of two propositions is not determined by the probabilities of those propositions). Two main directions in fuzzy logic have to be distinguished (cf. Zadeh 1994 Fuzzy logic in the broad sense (older, better known, heavily applied but not asking deep logical questions) serves mainly as apparatus for fuzzy control, analysis of vagueness in natural language and several other application domains. It is one of the techniques of soft-computing , i.e. computational methods tolerant to suboptimality and impreciseness (vagueness) and giving quick, simple and

8. Fuzzy Logic Fuzzy logic is basically a multivalued logic that allows intermediate values to be defined between conventional evaluations like yes/no, true/false, http://www.aaai.org/AITopics/html/fuzzy.html

Fuzzy Logic (a subtopic of Reasoning THE TOPICS AI in the news AI Overview Agents Applications Cognitive Science Education Ethical/Social Expert Systems FAQs History Interfaces Machine Learning Natural Language Philosophy Reasoning Reference Shelf Representation Resources Robots Science Fiction Speech Turing Test Vision What's Left? QUICK START tips AI Overview A - Z Index AAAI Video Archive AI in the news Doing a Report for School Site Map Reference Shelf How to use this site Search Engine DIRECTORY How to use this site A - Z Index Site Map Reference Shelf Search Engine Contact AI Topics Notices Disclosures AI Topics Home AAAI Home AAAI Video Archive XML/RSS news feed Good Places to Start Readings Online Related Web Sites Related Pages ... More Readings see FAQ Recent News about THE TOPICS (annotated) AI Topics home AAAI home ... engine "Fuzzy Logic is basically a multivalued logic that allows intermediate values to be defined between conventional evaluations like yes/no, true/false, black/white, etc. Notions like rather warm or pretty cold can be formulated mathematically and processed by computers." Bauer et al.

9. Fuzzy Logic Tutorial. Fuzzy logic list of books (through Amazon) http://www.fuzzy-logic.com/

FUZZY LOGIC TUTORIAL Fuzzy Logic for "Just Plain Folks" (Online Book, Free for your personal use.) By Thomas E. Sowell, Published on the Web 2003, revised 2006. Ch. 1 of 3. Fuzzy Logic - A Powerful Way to Analyze and Control Complex Systems Ch. 2 of 3. An Exciting Moment in the History of Science Ch. 3 of 3. Let's Build a Fuzzy Logic Controller comments or suggestions Counter provided courtesy of digits.com

10. Fuzzy Logic Knits logic is a Beautifully Fuzzy Thing. The Home of Mathematical Knitting, with Dr. SarahMarie Belcastro. Whom I would like to be when I grow up. http://www.fuzzylogicknits.com/

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11. What Is Fuzzy Logic ? Fuzzy logic is a powerful problemsolving methodology with a myriad of applications in embedded control and information processing. http://www.aptronix.com/fide/whatfuzzy.htm

What Is Fuzzy Logic ? Fuzzy logic is a powerful problem-solving methodology with a myriad of applications in embedded control and information processing. Fuzzy provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. In a sense, fuzzy logic resembles human decision making with its ability to work from approximate data and find precise solutions. Unlike classical logic which requires a deep understanding of a system, exact equations, and precise numeric values, Fuzzy logic incorporates an alternative way of thinking, which allows modeling complex systems using a higher level of abstraction originating from our knowledge and experience. Fuzzy Logic allows expressing this knowledge with subjective concepts such as very hot, bright red, and a long time which are mapped into exact numeric ranges. Fuzzy Logic has been gaining increasing acceptance during the past few years. There are over two thousand commercially available products using Fuzzy Logic, ranging from washing machines to high speed trains. Nearly every application can potentially realize some of the benefits of Fuzzy Logic, such as performance, simplicity, lower cost, and productivity. Fuzzy Logic has been found to be very suitable for embedded control applications. Several manufacturers in the automotive industry are using fuzzy technology to improve quality and reduce development time. In aerospace, fuzzy enables very complex real time problems to be tackled using a simple approach. In consumer electronics, fuzzy improves time to market and helps reduce costs. In manufacturing, fuzzy is proven to be invaluable in increasing equipment efficiency and diagnosing malfunctions.

12. Fuzzy Logic And Its Uses Fuzzy Rules Fuzzy Control Case Study A Smart Traffic Light Controller Adaptive Fuzzy Systems The Future References http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/sbaa/report.html

by Shahariz Abdul Aziz and Jeyakody Parthiban Introduction Background Case Study: A Smart Traffic Light Controller ... References

13. Fuzzy Logic: Product Information Fuzzy logic is Mathematica application software for creating Fuzzy sets and Fuzzy logic based systems. Graphics routines enable users to visualize Fuzzy http://www.wolfram.com/products/applications/fuzzylogic/

PreloadImages('/common/images2003/link_products_on.gif','/common/images2003/link_purchasing_on.gif','/common/images2003/link_forusers_on.gif','/common/images2003/link_aboutus_on.gif','/common/images2003/link_oursites_on.gif'); Products Fuzzy Logic What's New in Version 2? Features ... Give us feedback Sign up for our newsletter: The Most Flexible Environment for Exploring Fuzzy Systems Fuzzy Logic brings you an essential set of tools for creating, modifying, and visualizing fuzzy sets and fuzzy logic-based systems. Ideal for engineers, researchers, and educators, Fuzzy Logic provides practical examples that introduce you to basic concepts of fuzzy logic and demonstrate how to effectively apply the tools in the package to a wide variety of fuzzy system design tasks. Experienced fuzzy logic designers will find it easy to use the package to research, model, test, and visualize highly complex systems. The package's built-in functions help you at every stage of the fuzzy logic design process as you define inputs and outputs, create fuzzy set membership functions, manipulate and combine fuzzy sets and relations, apply inferencing functions to system models, and incorporate defuzzification routines. Ready-to-use graphics routines make it easy to visualize defuzzification strategies, fuzzy sets, and fuzzy relations. "This is the most useful computational package for the use and study of fuzzy logic by practicing professionals and students."

14. BBspot - Fuzzy Logic Archives A Very Special Fuzzy logic Fuzzy Arcade Mollytov Cocktail The Pin Slipped Caution Low Flying Geese Assault on Fort Dortmeyer http://www.bbspot.com/comics/fuzzy_logic/index.html

About BBlog BBloopers BBoard ... Archives Poll: What Do You Say? Your ad could be here, right now. BBlog WTF Hulu? ... Episode 0 ilovegreenpyro If I could be anywhere at the moment: "Eating my favorite foods with my friends while winning the lottery." ilovebluearson If I could be anywhere at the moment: "Eating my favorite foods with my friends while winning the lottery then rubbing it in their faces." Mockeries Archive BBcam Shop Amazon and Help BBspot ... Get Demotivators Subscribe Unsubscribe Hosted by: Politics Contact FAQs A D cash advance payday loans Private Krankenversicherung TOP Riester Rente Yahootemplates Web Templates Goverment Grants Internet Web Directory Web Templates ... Mortage Rate Deals 1999-2007 by BBspot LLC BBspot is a satire news and comedy source and meant to be funny. If you are easily offended, gullible or don't have a sense of humor we suggest you go elsewhere.

15. Open Site - Science: Mathematics: Logic: Fuzzy Logic Fuzzy logic is a superset of Boolean, or classical, logic dealing with the concept of partial truth. While in Boolean logic everything can be expressed in http://open-site.org/Science/Mathematics/Logic/Fuzzy_Logic

Enter your search terms Submit search form Web open-site.org home log in apply to edit Top ... Logic : Fuzzy Logic Fuzzy Logic is a superset of Boolean, or classical, logic dealing with the concept of partial truth. While in Boolean logic everything can be expressed in binary terms (0 or 1, on or off, yes or no), fuzzy logic replaces classical truth values with degrees of truth that range between and 1. Historical notes The subject was introduced by Lotfi Zadeh in the 1960s, and has been rather controversial since then. It is widely accepted within the engineering and computer science communities but generally rejected by mathematicians, a majority of which does not consider it a legitimate field of logic. addthis_url = location.href; addthis_title = document.title; addthis_pub = 'opensite'; All text is available under the terms of the GNU Free Documentation License . (See for details.) Hosted by Android Technologies, Inc. the medical robotics news source. Visit our sister sites dmoz.org

16. 'Fuzzy' Logic Article Researchers explore agricultural applications of new computer software technology. http://cati.csufresno.edu/upda/95/winter/story1.html

- Winter 1995 "Update" Newsletter Article - 'Fuzzy' logic Researchers explore agricultural applications of new computer software technology From CATI Publication #950101 A CSU, Fresno Industrial Technology professor is exploring agricultural applications of a new technology that mimics human thought patterns in controlling industrial equipment operations. Professor Matthew Yen's research is focused on the application of "fuzzy logic" in the control of equipment such as heaters, motors, pumps, valves and sprinklers used in the food processing industry and other automated agricultural operations. In order to automate these processes, temperature, motor speed, liquid level, pressure, humidity, flowrate and other variables must be constantly monitored and adjusted according to prescribed schedule. Simple on/off controls may overshoot, undershoot or fluctuate around the desired setting values. "Fuzzy logic control enables the system to tightly follow the control prescription in a smooth manner," Yen said. "It is an emerging technology widely used by the appliance industry and process industries in Japan." The concept fuzzy logic controls was first proposed in 1965 by L. A. Zadeh and is based on the "fuzzy estimation" or "chunking" of human thinking rather than precise mathematical computation. A control system based on fuzzy logic has the following advantages: 1) It is easy to implement since it uses "if-then" logic instead of sophisticated differential equations; 2) It is understandable by people who do not have process control backgrounds; and 3) Software and hardware tools are readily available for applying this technology.

17. PC AI - Fuzzy Logic Overview Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the uncertainty in data. It was introduced by Dr. Lotfi http://www.pcai.com/web/ai_info/fuzzy_logic.html

Where Intelligent Technology Meets the Real World Home Contents Search News ... Contact PC AI Fuzzy Logic Overview : Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the uncertainty in data. It was introduced by Dr. Lotfi Zadeh of UC/Berkeley in the 1960's as a means to model the uncertainty of natural language. Fuzzy logic is useful to processes like manufacturing because of its ability to handle situations that the traditional true/false logic can't adequately deal with. It lets a process specialist describe, in everyday language, how to control actions or make decisions without having to describe the complex behavior. See "Fuzzy Logic and Neural Networks - Practical Tools for Process Management" (PC AI May/June 1994, p. 17) for a clear and concise explanation of Fuzzy Logic. Glossary Link Fuzzy Logic SUBMIT YOUR SITE To Expert Systems To General AI Sites Fuzzy Logic Information on the Internet Applications for Fuzzy Logic An interesting list of applications in which fuzzy logic has played a role.

18. Fuzzy Logic Recordings free web site hit counter. http://www.fuzzylogicrecordings.com/

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19. Fuzzy Logic Functions: An Overview | The Brunching Shuttlecocks This function returns one of the nine neoboolean values used in Fuzzy logic true, false, maybe, sure, what, whoa, depends, http://www.brunching.com/fuzzylogic.html

Fuzzy Logic Functions: An Overview whatever whatever LIST This function returns one of the nine neo-boolean values used in fuzzy logic: true, false, maybe, sure, what, whoa, depends, look-let's-talk-about-this-later-when-we're-not-in-public, and elbows. The value returned is determined by standard anti-random vacillation routines. reconsider reconsider EXPR This causes the program to evaluate an expression until such time as it feels reasonably sure of its conclusion. Depending on the system and expression, this may take a fraction of a second or an entire freshman semester. while holdon while ( EXPR BLOCK holdon ( EXPR BLOCK This works like a standard while loop at first, but at some point the function realizes it's been bringing personal issues into the evaluation in an inappropriate manner and begins to evaluate the expression named by holdon instead in an attempt to appear reasonable. goaway goaway LABEL This causes the program to execute starting at LABEL , while making it clear to the program that you could care less whether it ever returned to the present execution point or not. Calling the apology function later may cause the program to return to the statement directly after the goaway , but it may also cause the program to exit entirely, depending on how much you've been taking it for granted. Use of this function has been generally deprecated since the publication of the landmark essay "'GOAWAY' Considered Thoughtless."

20. Fuzzy Logic The binary logic of modern computers often falls short when describing the vagueness of the real world. Fuzzy logic offers more graceful alternatives. http://www.fortunecity.com/emachines/e11/86/fuzzylog.html

web hosting domain names photo sharing Fuzzy Logic The binary logic of modern computers often falls short when describing the vagueness of the real world. Fuzzy logic offers more graceful alternatives. by Bart Kosko and Satoru Isaka BART KOSKO and SATORU ISAKA are pioneers in the development of fuzzy logic systems. Kosko holds degrees in philosophy and economics from the University of Southern California, a masters in applied mathematics from the University of California, San Diego, and a Ph.D. in electrical engineering from the University of California, Irvine. He is an assistant professor of electrical engineering at U.S.C., a governor of the International Neural Network Society and the program co-chair of the 1993 World Congress on Neural Networks. Isaka specializes in fuzzy information processing in the research and development division at Omron Advanced Systems in Santa Clara, Calif. He is interested in applying machine learning and adaptive control systems to biomedical systems and factory automation. He received his M.S. and Ph.D. degrees in systems science from U.C.S.D., in 1986 and 1989, respectively. Computers do not reason as brains do . Computers "reason" when they manipulate precise facts that have been reduced to strings of zeros and ones and statements that are either true or false. The human brain can reason with vague assertions or claims that involve uncertainties or value judgments: The air is cool," or "That speed is fast" or "She is young." Unlike computers, humans have common sense that enables them to reason in a world where things are only partially true.

21. QuickStudy: Fuzzy Logic Fuzzy logic is an extension of classic Boolean logic designed to work with imprecise or vague data. Where classical reasoning requires yes and no values, http://www.computerworld.com/databasetopics/data/software/story/0,10801,95497,00

@import url("/common/scripts/masthead.css"); @import url("/common/scripts/style.css"); document.write(''); document.write(''); document.write(''); document.write(''); More Resources Blogs Webcasts Quickstudies Security Manager's Journal This Week in Print Zones White Papers Editorial Calendar Events Research E-mail Newsletters Industry - Automotive - Defense/Aerospace - Energy/Utilities - Financial - Health Care - Retail - Transportation - Travel - Manufacturing - Small Enterprise document.write(''); Home News E-mail Newsletters Tech Dispenser ... Print Subscriptions Subscribe to our e-mail newsletters For more info on a specific newsletter, click the title. Details will be displayed in a new window. Computerworld Daily News (First Look and Wrap-Up) Computerworld Blogs Newsletter The Weekly Top 10 More E-Mail Newsletters Subscribe to Computerworld 40 years of the most authoritative source of news and information for IT leaders. QuickStudy: Fuzzy Logic Russell Kay or Other Databases Stories document.write(''); The Information Management Roadmap Eliminate Hidden Processes that Sap Up to 40% of Developers' Time Increase Customer Retention through Proactive SLA Management Information Management: Better Information for Winning Decisions. ... Sign up to receive Security Resource Alerts August 30, 2004 (Computerworld) More Computerworld QuickStudies Get Fuzzy If 0.70 represented a probability value, we would read it as "There is a 70% chance that Russell is short," meaning that we still believe that Russell is either short or not short, and we have a 70% chance of knowing which group he belongs to. But fuzzy terminology really translates to "Russell's degree of membership in the set of short people is 0.70," by which we mean that if we take all the (fuzzy set of) short people and line them up, Russell is positioned 70% of the way to the shortest.

22. ThinkGeek :: Fuzzy Logic Fuzzy logic extends that ability to computers by allowing for membership in more than one group. The room you re in can be both warm and suitable. http://www.thinkgeek.com/9ef5/

@import url(/css/base-import.css); @import url(/css/t-shirts-import.css); Account Wishlists Home About Us ... Site Index Navigate by Interest: ThinkGeek Exclusives Gifts for Him Gifts for Her Gifts for Kids Gifts Under $10 Gifts Under $20 Gifts Under $50 Gifts Under $100 Gifts Over $100 Geeks on the Go Gadget Freak Stuff for Students Web Developer DIY Goodies Monkeys Cool Retro Stuff! Our Favorites Binary Coder Goodies iPod Stuff For Your Home Gamer Mad Scientist TWiT Store Penny Arcade Store PVP Store Micro Goodies USB Devices Outdoor Geek Important Stuff: Gift Certificates Returns Info Customer Service You are not logged in. [ Log in Loot : Your cart is empty. Tshirts Science Fuzzy Logic Main Description Sizing Info Price: Availability: info In stock, except for the following item(s): Charcoal, XXL (Est. 1/18) Email me when available Choice: Please Select... Charcoal, S $14.99 Charcoal, M $14.99 Charcoal, L $14.99 Charcoal, XL $14.99 Charcoal, XXXL $16.99 Quantity: Buy this and earn Geek Points! what's this? Awesome-osity: Be one of the First to Write a Review Zoom IF closet IS running low THEN purchase shirt Computers reason in black and white. Humans, on the other hand, reason all the time in various shades of grey, with incomplete knowledge in a potentially unknown environment with imprecise elements. Fuzzy Logic extends that ability to computers by allowing for membership in more than one group. The room you're in can be both warm and suitable. Your laundry can be both wet and almost dry. While playing a video game, you can be both teh win over one player and pwned by someone else at the same time. Such is life.

23. Ortech Engineering's Fuzzy Logic Reservoir This part of the reservoir contains references to online papers, journals, and other publications. You should get a clear understanding of Fuzzy logic and http://www.ortech-engr.com/fuzzy/reservoir.html

Ortech Engineering Inc. Fuzzy Logic Reservoir Make sure your air tanks are full and take a deep breath before diving into this reservoir. Also be sure to string a return line during your exploration or you might never find your way back home. Gems located at this site are marked by a treasure chest all others will take you on a cyberdive. Enjoy your trip. Jump off the diving platform in one of the following directions to begin your adventure: The Diving Platform Enjoy Our Crystal Clear Waters On-line Papers, Journals, and other Publications Visit Our Coral Reefs Fuzzy Logic Labs at Universities See the Colorful Fish in the Sea A Virtual Who's Who of Fuzzy Logic on the Internet Discover the Lost Continent of Atlantis Fuzzy Logic Societies and Organizations Explore Underwater Caverns Fuzzy Logic Research Centers Relax and Visit With Other Divers Newsgroups and Archives Watch Out for the Sharks Commercial Product and Service Providers Our Crystal Clear Waters This part of the reservoir contains references to on-line papers, journals, and other publications. You should get a clear understanding of fuzzy logic and its applications from this information.

24. Fuzzy Logic A visual communications and brand development company specializing in new media. Site contains online portfolio. http://www.fuzzylogical.com/

25. Fuzzy Logic Provides substantial links related to Fuzzy logic. http://www.geocities.com/SiliconValley/Lakes/6007/Fuzzy.htm

FUZZY LOGIC INFORMATION NEWS GROUPS Short Definition Long Definition Executive Overview General Sources of Information ... Fuzzy CLIPS (free tool based on NASA CLIPS for crisp systems) fuzzyTech Home Page Related Links Electronic Newsletters Books With Disks ... Top of Page FUZZY LOGIC ELECTRONIC NEWSLETTERS Fuzzy Logic Newsletter To obtain samples of the Fuzzy Logic/Fuzzy Control Newsletter, send any e-mail message to fuz@ppgsoft.com . To subscribe to the Fuzzy Logic/Fuzzy Control Newsletter, send an e-mail with the Subject: "Subscribe FUZ" to subscribe@ppgsoft.com Technical University of Vienna Fuzzy Logic Mailing List ( listproc@dbai.tuwien.ac.at send get fuzzy-mail info NAFIPS Fuzzy Logic Mailing List ( listproc@listproc.gsu.edu send help For data mining list send an e-mail with an empty subject heading and: subscribe datamine-l in the body of the e-mail. Contact the Editor Adaptive Automation Home Page Technology Continuum Page Artificial Intelligence Book Store ... Top of Page

26. Fuzzy’s Logic Kubrickr Fuzzy vs Poker Blerk Files. Projects. Dystopia Info Agent Poker Projects. Meta. Login. Fuzzy’s logic is proudly powered by WordPress http://fuzzyslogic.com/

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27. Fuzzy Logic Inc. - Website Services Fuzzy logic Inc. supplier of website expertise and services to businesses in Calgary, Alberta. http://www.fuzzylogic.ca/

Logical solutions to fuzzy problems Website Services strategy, management, communications, user experience, maintenance About Fuzzy Logic About Micky Gulless Clients Writing for Websites and Email ... 5 Fallacies About Websites Calgary, Alberta , Canada info@fuzzylogic.ca Last change August 3, 2007 Posted February 8, 1999

28. CSISS Classics - Lotfi Zadeh: Fuzzy Logic-Incoporating Real-World Vagueness Professor Zadeh s paper on Fuzzy sets introduced the concept of a class with unsharp boundaries and marked the beginning of a new direction by providing a http://www.csiss.org/classics/content/68

Lotfi Zadeh: Fuzzy logic-Incoporating Real-World Vagueness By Pragya Agarwal Back to Classics Background Fuzzy logic was first invented as a representation scheme and calculus for uncertain or vague notions. It is basically a multi-valued logic that allows more human-like interpretation and reasoning in machines by resolving intermediate categories between notations such as true/false, hot/cold etc used in Boolean logic. This was seen as an extension of the conventional Boolean Logic that was extended to handle the concept of partial truth or partial false rather than the absolute values and categories in Boolean logic. Philosophers such as Plato had posited the laws of thought and one of these thoughts was the Law of Excluded Middle . Parminedes proposed the first version of this rule around 400 B.C. and stated amidst controversy that statements could be both true and not true at the same time. The Greek Philosopher Plato laid the foundations for the fuzzy logic by proposing a third region between true and false where the two notions tumbled together. In the early 1900s, Lukasiewicz extended on to the conventional bi-valued logic of Aristotle and proposed a tri-valued logic in his paper in 1920 titled On three-valued logic The fuzzy set theory was introduced by Professor Lotfi Zadeh in 1965 and can be seen as an infinite- valued logic. Lotfi Zadeh is currently serving as a director of BISC (Berkeley Initiative in Soft Computing). Prior to 1965 Zadeh's work had been centered on system theory and decision analysis. Since then, his research interests have shifted to the theory of fuzzy sets and its applications to artificial intelligence, linguistics, logic, decision analysis, control theory, expert systems and neural networks. Currently, his research is focused on fuzzy logic, soft computing, computing with words, and the newly developed computational theory of perceptions and natural language.

29. Fuzzy Logic The tutorial will introduce the basics of Fuzzy logic for data analysis. Fuzzy logic can be used to model and deal with imprecise information, http://videolectures.net/acai05_berthold_fl/

Log in Register HOME MOST POPULAR ... CONTACT US Fuzzy Logic author: Michael Berthold ACAI - 05 Description: The tutorial will introduce the basics of fuzzy logic for data analysis. Fuzzy Logic can be used to model and deal with imprecise information, such as inexact measurements or available expert knowledge in the form of verbal descriptions. We will first introduce the concepts of fuzzy sets, degrees of membership and fuzzy set operators. After discussions on fuzzy numbers and arithmetic operations using them, the focus will shift to fuzzy rules and how such systems of rules can be derived from available data. Categories Top Computer Science Fuzzy Logic You might be experiencing some problems with Your Video player. Slides Tutorial: Fuzzy Logic Overview Fuzzy Logic: Motivation Characteristic Functions: Crisp Sets Characteristic Functions: Fuzzy Sets Linguistic Variables and Values Types of Membership Functions Fuzzy Membership Function: Basic Concepts Operators on Fuzzy Sets - Page 1 Operators on Fuzzy Sets - Page 2 Min / Max-Norm Product / Bounded-Sum T-norms and S-norms Fuzzy T- and S-Norms - Page 1 Fuzzy T- and S-Norms - Page 2 Fuzzy Norms: Issues… Imprecise Reasoning Joint Constraint (support distribution) Conditional Constraint (possibility distribution) Joint vs. Conditional Constraint

30. FAQ: Fuzzy Logic And Fuzzy Expert Systems 1/1 [Monthly Posting] Archivename Fuzzy-logic/part1 Last-modified Fri Mar 14 113833 1997 by Mark Kantrowitz Version 1.27 Maintainer Mark Kantrowitz et al http://www.faqs.org/faqs/fuzzy-logic/part1/

Usenet FAQs Search Web FAQs Documents ... RFC Index FAQ: Fuzzy Logic and Fuzzy Expert Systems 1/1 [Monthly posting] There are reader questions on this topic! Help others by sharing your knowledge From: mkant+@cs.cmu.edu (Mark Kantrowitz) Newsgroups: comp.ai.fuzzy mkant+fuzzy-faq@cs.cmu.edu http://www.cs.cmu.edu/Web/Groups/AI/html/faqs/ai/fuzzy/part1/faq.html erik@syssoft.com ... ai+query@cs.cmu.edu with Send Fuzzy FAQ in the message body. The FAQ postings are also archived in the periodic posting archive on rtfm.mit.edu:/pub/usenet/news.answers/fuzzy-logic/ [18.181.0.24] If you do not have anonymous ftp access, you can access the archive by mail server as well. Send an E-mail message to mail-server@rtfm.mit.edu with "help" and "index" in the body on separate lines for more information. An automatically generated HTML version of the Fuzzy Logic FAQ is accessible by WWW as part of the AI-related FAQs Mosaic page. The URL for this resource is http://www.cs.cmu.edu/Web/Groups/AI/html/faqs/top.html fuzzynet@aptronix.com irwin@aptronix.com ftp.dhhalden.no:/pub/Fuzzy/ ... fuzzy@its.bldrdoc.gov . If you deposit anything in new/, please inform fuzzy@its.bldrdoc.gov. The repository is maintained by Timothy Butler, tim@its.bldrdoc.gov

31. Fuzzy Logic And Musical Decisions Abstract This article presents some of the core concepts of Fuzzy logic and demonstrates how they may be applied to problems common in music analysis and http://arts.ucsc.edu/ems/music/research/FuzzyLogicTutor/FuzzyTut.html

Fuzzy Logic and Musical Decisions Peter Elsea, University of California, Santa Cruz Abstract: This article presents some of the core concepts of Fuzzy Logic and demonstrates how they may be applied to problems common in music analysis and composition. Contents: Representation of pitches as sets Crisp and fuzzy logic Reasoning with Fuzzy Logic Using fuzzy reasoning to produce chord inversions. ... Further Study Representation of pitches as sets In the max environment, pitches are necessarily represented as numbers, typically by the MIDI code required to produce that pitch on a synthesizer. We must begin with and return to this representation, but for the actual manipulation of pitch data other methods are desirable, methods that are reflective of the phenomena of octave and key. A common first step is to translate the midi pitch number (mpn) into two numbers, representing pitch class (pc) and octave (oct) this is done with the formulas: oct = mpn / 12 pc = mpn % 12 The eventual reconstruction of the mpn is done by mpn = 12*oct + pc In this system pc can take the values - 11, in which represents a C. Oct typically ranges from to 10. Middle C, which is called C3 in the MIDI literature, and C4 by most musicians, is octave 5 after this conversion.

32. FuzzyTECH Complete Repository for Fuzzy logic Applications, including Application Notes, Simulation Software, and Teaching Materials. http://www.fuzzytech.com/

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33. FLLL - A Brief Course In Fuzzy Logic A brief course in Fuzzy logic and Fuzzy Control. Authors. Peter Bauer Stephan Nouak Roman Winkler. Version 1.2 Date December 4, 1996 http://www.esru.strath.ac.uk/Reference/concepts/fuzzy/fuzzy.htm

A brief course in Fuzzy Logic and Fuzzy Control Authors: Peter Bauer Stephan Nouak Roman Winkler Version: 1.2 Date: December 4, 1996 You may download this course from the FTP server ftp://ftp.flll.uni-linz.ac.at/pub/info/ Table of Contents Introduction Fuzzy Sets Basic definitions Operations on Fuzzy Sets Fuzzy Control Applications of Fuzzy Logic ... FLLL homepage

34. EUSFLAT - European Society For Fuzzy Logic And Technology 9th International Conference on Fuzzy Set Theory and Applications, Liptovský Mikuláš, Slovak Republic, February 48, 2008 http://www.eusflat.org/

EUSFLAT Newsletter Vol. 3, No. 3, December 2007 Four New EUSFLAT Working Groups 29th Linz Seminar on Fuzzy Set Theory, Linz, Austria, February 12-16, 2008 EUSFLAT 2007 Retrospect Member of the International Fuzzy Systems Association (IFSA)

35. Fuzzy Logic -- From Wolfram MathWorld In the Season 4 opening episode Trust Metric (2007) of the television crime drama NUMB3RS, math genius Charlie Eppes attempts to use Fuzzy logic in an http://mathworld.wolfram.com/FuzzyLogic.html

Search Site Algebra Applied Mathematics Calculus and Analysis ... Mathematics in Television Fuzzy Logic An extension of two-valued logic such that statements need not be true or false , but may have a degree of truth between and 1. Such a system can be extremely useful in designing control logic for real-world systems such as elevators. In the Season 4 opening episode " Trust Metric " (2007) of the television crime drama NUMB3RS, math genius Charlie Eppes attempts to use fuzzy logic in an attempt to construct a trust metric telling how much fugitive and alleged traitor Colby Granger can be trusted. SEE ALSO: Alethic False Logic True ... [Pages Linking Here] REFERENCES: Cignoli, R. L. O.; D'Ottaviano, I. M. L.; and Mundici, D. Algebraic Foundations of Many-Valued Reasoning. Dordrecht, Netherlands: Kluwer, 2000. Gottwald, S. A Treatise on Many-Valued Logics. Baldock, Hertfordshire, England: Research Studies Press, 2001. Metamathematics of Fuzzy Logic. Dordrecht, Netherlands: Kluwer, 1998. McNeill, D. Fuzzy Logic: A Practical Approach.

36. Free Fuzzy Logic Libarary The Free Fuzzy logic Library (FFLL) is an open source Fuzzy logic class library and API that is optimized for speed critical applications, such as video http://ffll.sourceforge.net/

Free Fuzzy Logic Library Home License History Class Hierarchy ... Downloads What is FFLL? The Free Fuzzy Logic Library (FFLL) is an open source fuzzy logic class library and API that is optimized for speed critical applications, such as video games. FFLL is able to load files that adhere to the IEC 61131-7 standard FFLL was a part originally released as part of the book: AI Game Programming Wisdom . A book containing over 650 pages of AI programming gems. Louder!'s own Michael Zarozinski contributed a chapter detailing the fuzzy logic class libraries that Spark! was built upon. What do you want to know more about? Contributing to the development of FFLL Getting FFLL License Class Hierarchy ... The company behind FFLL What's New August 8, 2003 FFLL V2.2.1 released Spark! Viewer download available - see what your fuzzy logic models look like! Sample FCL and projects files posted Louder Than A Bomb! Software

37. Fuzzy Logic | This Headline Is (half) False | Economist.com In order to gain access to it please either Log in, Activate your complimentary web account if you are a print subscriber, or Subscribe now. Fuzzy logic http://www.economist.com/science/displaystory.cfm?story_id=2099851

38. Type-2 Fuzzy Logic An online information resource on type2 Fuzzy logic. http://www.type2fuzzylogic.org/

Home Publications News Events ... Contact Site Index Home Publications People News ... Contact Members Area Username: Password: Remember me Register here Forgotten your password? Site Hosted By Introduction Type2fuzzylogic.org seeks to provide the type-2 fuzzy logic community with a focal point for research, announcements and discussions. It is aimed at those already active in the field to keep abreast of developments as well as a useful resource for those new to type-2 fuzzy logic. This is your site and we hope you provide information on papers we may have missed, news items and announcements of conferences etc, This site provides the following resources: A community maintained database of type-2 publications. A type-2 fuzzy logic news page. A list of forthcoming events, conferences, etc. A list of type-2 fuzzy practitioners that have signed up to this site. An interactive forum for discussing issues surrounding type-2 fuzzy logic. We hope you will find this site useful and interesting. This usefulness of this site relies on contributions from the community. Please take the time to register on this site and to submit content. You can contact us here , we look forward to your comments and suggestions.

39. Fuzzy Logic Software: Type-2 Fuzzy Logic Software! Freeware! Fuzzy logic software! Type2 Fuzzy logic software will let you handle rule uncertainties using Fuzzy memberships. http://sipi.usc.edu/~mendel/software/

Type-2 Fuzzy Logic Software Nilesh N. Karnik, Qilian Liang, Feilong Liu and Jerry M. Mendel mendel@sipi.usc.edu Type-2 Fuzzy Logic Software Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions Book Type-2 Fuzzy Logic Software Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions Book Type-2 Fuzzy Logic Software Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions Book W e are providing software (freeware) on-line so that you can immediately begin using type-2 fuzzy logic. It is in four sections: general type-2 fuzzy logic systems, interval type-2 fuzzy logic systems, type-1 fuzzy logic systems, and NEW type-reduction. This software is experimental in nature and is provided on an "as is" basis only. The University SPECIFICALLY DISCLAIMS ALL WARRANTIES INCLUDING, WITHOUT LIMITATION, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. B y accessing the software, you agree to abide by the conditions of the three numbered items. Select one of the following two choices. Selecting the first choice provides you with the software. Selecting the second choice sends you to the report page.

40. Math Forum - Ask Dr. Math Date 04/26/97 at 033006 From Nicholas Graham Subject Fuzzy logic My calculus teacher suggested that when I get onto the Internet, I look up Dr. Math http://mathforum.org/library/drmath/view/51449.html

Associated Topics Dr. Math Home Search Dr. Math Fuzzy Logic Date: 04/26/97 at 03:30:06 From: Nicholas Graham Subject: Fuzzy logic My calculus teacher suggested that when I get onto the Internet, I look up Dr. Math and ask about fuzzy logic. He said the reply would be interesting. Well, here I am asking. Thank you! Nick Graham, Grade 11 Calculus Student Date: 04/26/97 at 10:07:53 From: Doctor Sarah Subject: Re: Fuzzy logic Hi Nick - Let's get you started exploring the internet. Using Altavista http://altavista.digital.com/ to search for "fuzzy logic" (we recommend that you use a searcher for a topic like this, since there's lots on the Web about it!) here are just a few examples of what you can find: (1) Fuzzy logic basics http://www.austinlinks.com/Fuzzy/basics.html "Fuzzy Logic is a departure from classical two-valued sets and logic, that uses "soft" linguistic (e.g. large, hot, tall) system variables and a continuous range of truth values in the interval [0,1], rather than strict binary (True or False) decisions and assignments. Formally, fuzzy logic is a structured, model-free estimator that approximates a function through linguistic input/output associations. Fuzzy rule-based systems apply these methods to solve many types of "real-world" problems, especially where a system is difficult to model, is controlled by a human operator or expert, or where ambiguity or vagueness is common. A typical fuzzy system consists of a rule base, membership functions, and an inference procedure" (2) Fuzzy logic

41. Fuzzy Logic Sources Of Information My personal Fuzzy logic bibliography is available here mainly references to type 2 and interval valued Fuzzy sets but also some other relating to http://www.cse.dmu.ac.uk/~rij/fuzzy.html

42. Fuzzy Logic - A Definition From WhatIs.com Fuzzy logic is an approach to computing based on degrees of truth rather than the usual true or false (1 or 0) Boolean logic on which the modern computer is http://whatis.techtarget.com/definition/0,,sid9_gci212172,00.html

fuzzy logic Search our IT-specific encyclopedia for: or jump to a topic: Application Security CIO CRM Data Center Data Management Domino Exchange IBM S/390 IBM AS/400 IT Channel Mobile Computing Networking Networking Channel Open Source Oracle SAP Security Security Channel Server Virtualization Small Medium Business SQL Server Storage Storage Channel Systems Channel Visual Basic VoIP Web Services Windows IT Windows Security Windows Systems Advanced Search Browse alphabetically: A B C D ... Programming fuzzy logic Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based. The idea of fuzzy logic was first advanced by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1960s. Dr. Zadeh was working on the problem of computer understanding of natural language. Natural language (like most other activities in life and indeed the universe) is not easily translated into the absolute terms of and 1. (Whether everything is ultimately describable in binary terms is a philosophical question worth pursuing, but in practice much data we might want to feed a computer is in some state in between and so, frequently, are the results of computing.) Fuzzy logic includes and 1 as extreme cases of truth (or "the state of matters" or "fact") but also includes the various states of truth in between so that, for example, the result of a comparison between two things could be not "tall" or "short" but ".38 of tallness."

43. Fuzzy Logic Tutorial A 6part tutorial on Fuzzy logic covering sets, rule matrices, membership functions, A instructive paper on Fuzzy logic (by Tung Tran and Ali Zomorodi). http://www.cs.cofc.edu/~manaris/ai-education-repository/fuzzy-tutorial.html

Go Home Fuzzy Logic This site is no longer being maintained. Sorry. OUTLINE TUTORIAL TOOLS RESOURCES ... SUBMIT Tutorials A 6-part tutorial on fuzzy logic covering sets, rule matrices, membership functions, etc. Also has some sample problems. A fuzzy tutorial with an explanation of fuzzy sets. A brief course in Fuzzy Logic. A instructive paper on fuzzy logic (by Tung Tran and Ali Zomorodi). A large archive of fuzzy logic tutorials. Submit Submit a tutorial on Fuzzy Logic. Last updated on Tuesday, April 13, 2004 04:06:50 PM. Suggestion Box visitors since April 8, 1999 (counter provided by LinkExchange

44. Index.html.new The FuzzyJ Toolkit is a set of Java(tm) classes that can be used to build Fuzzy logic systems. The toolkit s API can be used standalone to create Fuzzy http://ai.iit.nrc.ca/IR_public/fuzzy/

Fuzzy Logic in Integrated Reasoning FuzzyCLIPS FuzzyCLIPS is an extension of the CLIPS bob.orchard@nrc.ca FuzzyJ Toolkit for the Java(tm) Platform and FuzzyJess The FuzzyJ Toolkit is a set of Java(tm) classes that can be used to build fuzzy logic systems. The toolkit's API can be used standalone to create fuzzy rules and perform fuzzy reasoning. It can also be used with Jess , the Expert System Shell from the Sandia National Laboratories providing a capability that is similar to but in many ways more flexible than FuzzyCLIPS. This integration with Jess, FuzzyJess , has been carefully planned with the Jess author so that the effort to maintain and follow Jess revisions will require minimal effort. The toolkit is currently at version 1.10a (***NEW*** as of September 5, 2006). User feedback is welcomed and will help us shape future versions of the FuzzyJ Toolkit. Comments and questions should be addressed to bob.orchard@nrc-cnrc.gc.ca Last modified: September 5, 2006.

45. Fuzzy-Logik - Wikipedia Translate this page Zuvor hatte Joseph Goguen, ein Doktorand von Zadeh, eine „logic of inexact concepts“ eingeführt. Heute wird die Fuzzy-Logik oder Fuzzy-Control vorwiegend http://de.wikipedia.org/wiki/Fuzzy-Logik

var wgNotice = ""; var wgNoticeLocal = ""; var wgNoticeLang = "de"; var wgNoticeProject = "wikipedia"; Fuzzy-Logik aus Wikipedia, der freien Enzyklop¤die Wechseln zu: Navigation Suche Fuzzy-Logik (englisch: fuzzy = unscharf ) ist eine Theorie, eine Verallgemeinerung der zweiwertigen Booleschen Logik , die vor allem f¼r die Darstellung menschlichen (und damit unscharfen) Wissens entwickelt wurde. Fuzzy-Computersysteme verarbeiten gegen¼ber herk¶mmlichen Systemen nicht nur Werte wie JA und NEIN (oder AN und AUS oder 1 und ), sondern zus¤tzlich als Zwischenwert (Wahrheitswert) zwischen WAHR (=1) und FALSCH (=0) etwa , so dass damit auch unscharfe Angaben wie EIN BISSCHEN, ZIEMLICH oder STARK mathematisch behandelt werden k¶nnen (vgl. auch Fuzziness (Sprache) ). Damit arbeiten fuzzylogikunterst¼tzte Programme n¤her am menschlichen Denken als ¼bliche Programme. Die Fuzzy-Set-Theorie , also die unscharfe Mengenlehre , wurde bereits 1965 von L. A. Zadeh , einem aus Aserbaidschan stammenden Professor f¼r Elektrotechnik an der University of California, Berkeley

46. Fuzzy Logic - A Comic By Mike Stanfill Fuzzy logic by Mike Stanfill ©2002. 1 • 2 • 3 • 4 • 5 • 6 • 7 • 8 • 9 • 10 • 11 • 12 • 13 • 14 • 15 • 16 • 17 • 18 http://www.privatehand.com/comics/fuzzy_logic/fuzzy01.html

47. Intelligent Solutions, Inc. Petroleum & Natural Gas Engineering Consultant Fuzzy logic is the focus of this article. An overview of the subject is provided In this article, application of Fuzzy logic for restimulation candidate http://www.intelligentsolutionsinc.com/part3.htm

Distinguished Author Series JPT - Journal of Petroleum Technology, November 2000 VIRTUAL INTELLIGENCE AND ITS APPLICATIONS IN PETROLEUM ENGINEERING Part 3. Fuzzy Logic Shahab Mohaghegh INTELLIGENT SOLUTIONS, INC. West Virginia University In two previous articles, a general overview of artificial neural networks and evolutionary computing and their applications in the oil and gas industry was presented. Fuzzy logic is the focus of this article. An overview of the subject is provided followed by its potential application in solving petroleum engineering related problems. As it was mentioned in the previous articles, the most successful applications of intelligent systems, especially when solving engineering problems, have been achieved by using different intelligent tools in concert and as a hybrid system. In this article, application of fuzzy logic for restimulation candidate selection in a tight gas formation in the Rocky Mountains will be reviewed. This particular application was chosen because it uses fuzzy logic in a hybrid manner integrated with neural networks and genetic algorithms. BACKGROUND The science of today is based on Aristotle’s crisp logic formed more than two thousand years ago. The Aristotelian logic looks at the world in a bivalent manner, such as black and white, yes and no, and and 1. Development of the set theory in the late 19

48. Neusciences - Business Intelligence Software, Gather - Analyse - Forecast - Grow Neusciences are one of the UK s leading developers of advanced analytics software. Our browserbased business intelligence packages support good decision http://www.neusciences.com/

Home Products Industries Applications ... Contact Business intelligence software gather - analyse - forecast - grow The quicker you understand the trends, the faster you can make the next intelligent move In markets from FMCG to automotive, Neusciences' intelligent software tools help businesses make better decisions. Our business intelligence package - Investigator II - captures business data, for faster analysing, better demand forecasting, stock management, and competitive analysis. And browser-based access makes it easy to install and very friendly to use. Our knowledge software will empower you, with automated, intelligent help to streamline the management of your business. See for yourself! Why not put Investigator to the test? Talk to us about a free, hands-on demonstration geared specifically to your business, your needs, and your data. "Investigator helped us to reduce our stock holdings by four weeks." A major pharmaceutical vendor What's your market? Brewing Automotive Health Pharmaceuticals What's your application? Analytics Demand Forecasting Market Analysis Our portfolio at a glance Investigator II - business data analysis and forecasting Optimiser II - demand planning, tracking and

49. Fuzzy Multidimensional Logic Bivalent, or two state, logic is just a subset of the more powerful methods of Fuzzy logic, introduced here, which reject the law of the excluded middle. http://www.calresco.org/lucas/fuzzy.htm

Fuzzy Multidimensional Logic by Chris Lucas "No assertion is ever known with certainty... but that does not stop us making assertions." Carneades, 214-129 BCE "The facts were always fuzzy or vague or inexact... Science treated the gray or fuzzy facts as if they were the black-white facts of math. Yet no one had put forth a single fact about the world that was 100% true or 100% false." Bart Kosko, Fuzzy Thinking, 1994, Preface Introduction Logic to most people relates to two state thinking, the idea that the outcome can only be either true or false, 1 or 0, right or wrong. This form of logic dates back to ancient Greece and is perfectly adequate to answer simple questions in single dimensions, for example, if A is 1 and B is what is A AND B ? It can be extended, as is done in Boolean algebra to more complex questions, as long as all the parts can be described using the same restricted alphabet of two symbols. Such logic is a deductive way of understanding consequences, and a highly valuable intellectual technique. But this sort of logic is inadequate when we need to reason about variables that have more than two values, or in cases where multiple incompatible variables are involved. Yet we still need to make decisions in these cases, so how can we proceed ? Bivalent, or two state, logic is just a sub-set of a more powerful type of logic known as fuzzy logic, so here we will introduce this subject and show how it can be used to evaluate choices both in the multi-valued scenarios of one variable and more importantly in the multi-dimensional scenarios common to complex systems incorporating multiple variables.

50. Definition: Fuzzy Logic From Online Medical Dictionary These ordinary terms represent Fuzzy sets in a particular problem. Fuzzy logic plays a key role in many medical expert systems. (12 Dec 1998) http://cancerweb.ncl.ac.uk/cgi-bin/omd?fuzzy logic

51. Article#2 On Fuzzy Logic And Its Uses This article describes the procedures required in designing Fuzzy logic machines starting with the basics, Fuzzy rules, moving on to the Fuzzy controller http://www-dse.doc.ic.ac.uk/~nd/surprise_96/journal/vol2/sbaa/article2.html

Everything You've Always Wanted to know About Designing Fuzzy Logic Machines But Were Afraid to Ask [Abstract] [Fuzzy Rules] [Fuzzy Control] [Case Study: Fuzzy Traffic Light Controller] Abstract The Smart Air Conditioner : automatically adjusts the flow of air according to the surrounding temperature. The Smart TV : adjusts its contrast and colour modes for every new frame. The Smart Washing Machine : adds more detergent when there is more dirt. All with the push of a button. Great!!! We are witnessing a miracle in technology. Too good to be true. But enough!!! How do such miracles occur? How complicated is the math ? HOW DOES IT WORK!!!! This article describes the procedures required in designing fuzzy logic machines starting with the basics, fuzzy rules, moving on to the fuzzy controller and finally considering a case study where a real life useful application of fuzzy logic is applied. Fuzzy Rules Human beings make descisions based on rules. Even though, we may not be aware of it, all the descisions we make are based on computer like if-then statements. If the weather is fine, then we may decide to go out. If the forecast says the weather will be bad today, but fine tommorow, then we make a descision not to go today, and postpone it till tommorow. Rules associate ideas and relate one event to another. Fuzzy machines, which always tend to mimick the behaviour of man, work the same way. Only this time the descision and the means of choosing that descison are replaced by fuzzy sets and the rules are replaced by fuzzy rules. Fuzzy rules also operate using a series of if-then statements. For instance, X then A, if y then b, where A and B are all sets of X and Y. Fuzzy rules define fuzzy

52. XpertRule Software Ltd | Fuzzy Logic Humans can reason very effectively with such Fuzzy definitions, therefore, in order to capture human Fuzzy reasoning we need Fuzzy logic. http://www.xpertrule.com/pages/fuzzy.htm

Home Contact Products User Stories ... About Us White Paper: Fuzzy Logic in Knowledge Builder Rule based logic has been used to capture human expertise in classification, assessment, diagnostic and planning tasks. Probability has traditionally been used to capture decision making under uncertain conditions. For example, consider the rule: IF Symptom-A is present THEN diagnosis is illness-X There will be situations in which we are uncertain about the presence of Symptom-A. In such cases we can enter the probability of Symptom-A being present which will result in a confidence factor in our diagnosis of illness-X. A number of methods have been used to propagate probabilities during rule based inference. Many of these techniques are based on the probabilistic inference techniques used in Mycin and Prospector . The weakness of such techniques is that they do not reflect the way human experts reason under uncertainty. XpertRule Knowledge Builder allows an alternative methodology to the probabilistic reasoning approach. This involves defining Symptom-A and illness-X as logical attribute with values

53. Fuzzy Sets And Fuzzy Logic This section contains an overview of Fuzzy Sets and Fuzzy logic. This information is taken from Fuzzy Sets and Fuzzy logic Theory and Applications, http://members.aol.com/btluke/fuzzy01.htm

Fuzzy Sets and Fuzzy Logic Brian T. Luke, Ph.D. ( btluke@aol.com LearningFromTheWeb.net This section contains an overview of Fuzzy Sets and Fuzzy Logic. This information is taken from Fuzzy Sets and Fuzzy Logic: Theory and Applications , George J. Klir and Bo Yuan, Prentice Hall, NJ (1995) Given three fuzzy sets (A, B, C), they each have associated membership functions (Ma, Mb, Mc). Since there is no ambiguity, A can be interchanged with Ma, B with Mb, and C with Mc. Therefore, throughout this text, A represents both a fuzzy set and its associated membership function. If x is the parameter or value that determines which set(s) the data belongs to, the membership functions can be written as A(x), B(x), and C(x). An alpha-cut of the membership function A (denoted aA)