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	Encyclopedia article: Fuzzy control system (Site not responding. Last check: 2007-10-10)
		Fuzzy logic (A form of mathematical logic in which truth can assume a continuum of values between 0 and 1) is a way of interfacing inherently analog processes, that move through a continuous range of values, to a digital computer to perform tasks, based on abstracted values, as if they were well-defined discrete numeric values.
		Interest in fuzzy systems was sparked by Seiji Yasunobu and Soji Miyamoto of Hitachi, who in 1985 provided simulations that demonstrated the superiority of fuzzy control systems for the Sendai railway.
		Their ideas were adopted, and fuzzy systems were used to control accelerating, braking, and stopping when the line opened in 1987.
	www.absoluteastronomy.com /encyclopedia/f/fu/fuzzy_control_system.htm (3028 words)

	Fuzzy control system - Wikipedia, the free encyclopedia
		Fuzzy logic is a way of interfacing inherently analog processes, that move through a continuous range of values, to a digital computer to perform tasks, based on abstracted values, as if they were well-defined discrete numeric values.
		Fuzzy logic was first proposed by Lotfi A. Zadeh of the University of California at Berkeley in a 1965 paper.
		Fuzzy systems were largely ignored in the U.S. because they were associated with artificial intelligence, a field that periodically oversells itself and which did so in a big way in the mid-1980s, resulting in a lack of credibility within the commercial domain.
	en.wikipedia.org /wiki/Fuzzy_control_system (3240 words)

	Fuzzy logic - Wikipedia, the free encyclopedia
		Fuzzy logic allows for set membership values between and including 0 and 1, shades of gray as well as fl and white, and in its linguistic form, imprecise concepts like "slightly", "quite" and "very".
		Fuzzy logic is controversial despite wide acceptance: it is rejected by some control engineers for validation and other reasons, and by some statisticians who hold that probability is the only rigorous mathematical description of uncertainty.
		Fuzzy logic can be used to control household appliances such as washing machines (which sense load size and detergent concentration and adjust their wash cycles accordingly) and refrigerators.
	en.wikipedia.org /wiki/Fuzzy_logic (1841 words)

	Fuzzy Expert System for Navigation Control
		Fuzzy logic technology is one of the AI (Artificial Intelligence) techniques first developed by Lotfi Zadeh in 1965.
		Fuzzy logic has been successfully applied to a large number of diverse applications such as nuclear reactor control, ship crane control, subway system control, chemical process control, domestic appliances and navigation control.
		The microcontroller used is 87C251SB from Intel and the fuzzy add-ons are implemented on XC4003EPC84, an FPGA from Xilinx.
	www.geocities.com /SiliconValley/Lakes/6165/khkoay_project.html (2941 words)

	Fuzzy (Site not responding. Last check: 2007-10-10)
		Fuzzy dice are the precursor to a number of...
		Fuzzy felt Fuzzy Felt is a popular felt, typically printed with a picture such as a farmyard scene, is given a card back...
		Fuzzy game In 0: it is not greater than 0, which would be a win for Left; nor less than 0 which would be a win for Right...
	www.brainyencyclopedia.com /topics/fuzzy.html (165 words)

	FAQ: Fuzzy Logic and Fuzzy Expert Systems 1/1 [Monthly posting] - [4] What is a fuzzy expert system?
		In SUM composition, the combined output fuzzy subset is constructed by taking the pointwise sum over all of the fuzzy subsets assigned to the output variable by the inference rule.
		In the composition subprocess, all of the fuzzy subsets assigned to each output variable are combined together to form a single fuzzy subset for each output variable.
		In MAX composition, the combined output fuzzy subset is constructed by taking the pointwise maximum over all of the fuzzy subsets assigned to the output variable by the inference rule.
	www.cs.cmu.edu /Groups/AI/html/faqs/ai/fuzzy/part1/faq-doc-4.html (1209 words)

	Fuzzy Logic
		Saying “yes” (which is the mainstream of fuzzy logic) one accepts the truth-functional approach; this makes fuzzy logic to something distinctly 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).
		Fuzzy logic in the narrow sense is symbolic logic with a comparative notion of truth developed fully in the spirit of classical logic (syntax, semantics, axiomatization, truth-preserving deduction, completeness, etc.; both propositional and predicate logic).
		This fuzzy logic is a relatively young discipline, both serving as a foundation for the fuzzy logic in a broad sense and of independent logical interest, since it turns out that strictly logical investigation of this kind of logical calculi can go rather far.
	plato.stanford.edu /entries/logic-fuzzy (2595 words)

	FAQ: Fuzzy Logic and Fuzzy Expert Systems 1/1 [Monthly posting]
		Fuzzy Subsets: Just as there is a strong relationship between Boolean logic and the concept of a subset, there is a similar strong relationship between fuzzy logic and fuzzy subset theory.
		Fuzzy control replaces, in the picture above, the role of the mathematical model and replaces it with another that is build from a number of smaller rules that in general only describe a small section of the whole system.
		The fuzzy logic community states that these logical equivalence axioms are not required in fuzzy logic, and that Elkan's proof requires the excluded middle law, a law that is commonly rejected in fuzzy logic.
	www.faqs.org /faqs/fuzzy-logic/part1 (8990 words)

	MEDEX: A Fuzzy Expert System
		A fuzzy set is a set whose elements might only partially belong to that set, as opposed to the more traditional nonfuzzy set, where the elements are either completely inside or completely outside of the set.
		As a result, the fuzzy set allows for a smoother transition out of SMALL for pressure gradient ranging between 3 mb and 7 mb, as shown in the right portion of the graph.
		Fuzzy set methodology allows imprecision in user input as well as imprecision in the expert system rule base specification.
	www.nrlmry.navy.mil /~medex/tutorial/medex/fuzzy.html (495 words)

	EDN -- 11.10.94 Dismantling a fuzzy rule-based system shows its inner workings
		You express rules using fuzzy terms, such as "if Rotational_Velocity is High then..." You perform fuzzification, or transformation from crisp to fuzzy values, by identifying to what degree the crisp value is a member of each of the fuzzy sets.
		The system samples inputs at each sampling interval and applies those inputs to the appropriate input membership sets to determine their degrees of membership in each set.
		When several rules fire at once, as is often the case in a fuzzy system, their actions must combine into a single action.
	www.edn.com /archives/1994/111094/23column.htm (1729 words)

	Xiaoguang'Publication
		The goal of system identification is to derive the system model or behavior from observed input-output data via some machine learning tools.
		System model is an important topic in the control communities.
		Above mentioned that fuzzy system can integrate some priori knowledge on the system into their structures, but some “free” parameter learning strategies can freely select the structures, tune parameters, and thus inevitably destroyed these integrated knowledge.
	www.louisville.edu /~x0chan01/res/si.htm (835 words)

	Amazon.com: The Fuzzy Systems Handbook: A Practitioner's Guide to Building, Using, & Maintaining Fuzzy Systems: Books: ... (Site not responding. Last check: 2007-10-10)
		Fuzzy logic is controversial, since the validity of its methods, except in the most trivial cases, are unprovable in terms of classic control theory.
		He has cleaned up the discussions of importance of structure of fuzzy sets, how they should be built for some kinds of applications, why bell-shaped and trapezoidal membership sets are important in business fuzzy sets while engineers tend to choose triangular sets.
		In this introductory chapter we discuss the rationale behind fuzzy system modeling, introduce the ideas of a fuzzy set and a linguistic variable, differentiate between fuzzy logic and the more general area of approximate reasoning, briefly trace the history of fuzzy set theory, and outline the benefits of using fuzzy logic in information system modeling.
	www.amazon.com /exec/obidos/tg/detail/-/0121944557?v=glance (1916 words)

	Fuzzy Anti-Lock Brake System Solution
		Although fuzzy logic is rigorously structured in mathematics, one advantage is the ability to describe systems linguistically through rule statements.
		As linguistic descriptions of a system are much easier to produce than complex mathematical models, fuzzy logic has great appeal for controlling complex systems as changes in the system have little if any effect upon the algorithm.
		ABS systems were introduced to the commercial vehicle market in the early 1970's to improve vehicle braking irrespective of road and weather conditions.
	developer.intel.com /design/mcs96/designex/2351.htm (2351 words)

	Fuzzy Logic: Product Information
		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.
		This interactive document format not only is useful to professionals working on a complex fuzzy model but also is ideal for presenting concepts to students and allows them to turn in completed homework assignments and lab reports either electronically or on paper as a printed notebook.
		Fuzzy Logic 2.0.2 requires Mathematica 5.0 or higher and is available for all Mathematica platforms.
	www.wolfram.com /products/applications/fuzzylogic (317 words)

	Mapping Land Units within Land Systems in Central Queensland Using a Fuzzy Expert System and Terrain Models
		A fuzzy rule-based system was developed to classify the raster data sets and consequently to map the likely occurrence of land facets within each land unit.
		The rules were derived from the specific relationships between landform and facet described in the land system survey, and modified according to visual inspection of the terrain data sets, remote sensing images, aerial photographs, and several field traverses.
		The membership functions and rules were codified in fuzzy system software and a final membership in each facet class was generated using fuzzy algebra.
	www.essc.psu.edu /pedometrics/abstracts/html/grundy.html (708 words)

	Ortech Engineering's Fuzzy Logic Reservoir
		Center for Fuzzy Logic, Robotics, and Intelligent Systems Texas A&M University's CFL coordinates research activities at TAMU on fuzzy logic and its application in engineering systems.
		Fuzzy Logic Sources of Information A large list of on-line fuzzy logic resources by Robert John at De Montfort University in the UK.
		Fuzzy CLIPS by the IIT of NRC This version of Fuzzy CLIPS was developed by the Institute for Information Technology of the National Research Council in Canada.
	www.ortech-engr.com /fuzzy/reservoir.html (949 words)

	Fuzzy Expert Systems
		In other words, a fuzzy expert system is a collection of membership functions and rules that are used to reason about data.
		In a fuzzy expert system, the inference process is a combination of four subprocesses: _fuzzification_, _inference_, _composition_, and _defuzzification_.
		Sometimes it is useful to just examine the fuzzy subsets that are the result of the composition process, but more often, this _fuzzy value_ needs to be converted to a single number - a _crisp value_.
	www.austinlinks.com /Fuzzy/expert-systems.html (1454 words)

	EDN Access 09.01.95 Embedding a fuzzy design
		Other fuzzy development tools provide partial support to embedded systems, primarily by generating C code of the developed fuzzy system.
		Now comes your second decision, which is whether to structure the fuzzy system as an interpreter or to use inline code.
		In general, interpreted systems are slower but more memory-efficient, enhance the ability to make and test modifications with table changes rather than a modify/compile/link/ download sequence, and require a fuzzy kernel, which can be assembly-language-optimized for speed.
	www.edn.com /archives/1995/090195/18column.htm (997 words)

	RESPONSE OF AGC TO A FUZZY CONTROLLER IN AN INTER-CONNECTED SYSTEM AFTER DEREGULATION
		The role of AGC is to divide the loads among the system, station and generator to achieve maximum economy and accurate control of the scheduled interchanges of tie-line power while maintaining a reasonability uniform frequency.
		The inputs to the fuzzy controller generally are error and change in error of frequency [paper 9-11] but here we have used change in frequency and change in tie line power i.e.
		However the aggregate of a fuzzy set encompass3s a range of output value, which is defuzzified in order to resolve a single output valve from the set.
	www.acadjournal.com /2005/v15/part1/p2 (2330 words)

	Aptronix home page
		fuzzy logic technology and system designs using FIDE™ and other tools.
		But you need software to build a fuzzy system and hardware to build a very large and fast one.
		Everything is under one roof: graphic representation of the system, functions and rules, traceability from the most abstract to the lowest levels, and the easy ability to link to other systems.
	www.aptronix.com (248 words)

	CRISP & FUZZY SYSTEMS ENGINEERING (Site not responding. Last check: 2007-10-10)
		The Fuzzy Thought Amplifier is a uniquely new and totally different application of fuzzy logic.
		This file is needed for the construction of the fuzzy associative memory or fuzzy estimation surface in your application.
		Fuzzy systems use fuzzy estimation and control transforms.
	www.fuzzysys.com (818 words)

	Fuzzy Shower
		The code for this demo is entirely Java(tm) code, although there is a capability to create more sophisticated rule based expert systems in concert with Jess (Expert System Shell) from Sandia National Laboratories (see the associated demo of the hybrid Java/Jess Fuzzy Shower).
		These rules are not really adequate or optimized in any way, but with them and some simple coded heuristics for checking error situations, they do a good job of keeping the shower under control.
		When in auto Fuzzy control mode things happen very fast and it is difficult to see all that is happening.
	ai.iit.nrc.ca /IR_public/fuzzy/fuzzyShower.html (322 words)

	literature - fuzzynet (Site not responding. Last check: 2007-10-10)
		Industrial Applications of Fuzzy Logic and Intelligent Systems, by John Yen, Reza Langari, Lotfi A. Zadeh (Editor), Paperback, 356 pages, IEEE Press, April 1,1995, ISBN: 0-7803-1048-9.
		The Fuzzy Systems Handbook : A Practitioner's Guide to Building, Using, and Maintaining Fuzzy Systems, by Earl Cox, BookandDisk Edition, Paperback, Published by Ap Professional, February 1,1994, ISBN: 0121942708.
		Fuzzy Inference Language (FIL) is the language that is used by Aptronix's proprietary software - Fuzzy Inference Development Environment (FIDE).
	www.aptronix.com /fuzzynet (340 words)

	Citebase - Obtaining Membership Functions from a Neuron Fuzzy System extended by Kohonen Network
		The model is tested by simulating real systems, here represented by a nonlinear mathematical function.
		Comparison with the results obtained by traditional neural networks, and correlated studies of neurofuzzy systems applied in system identification area, shows that the NFN-MK model has a similar performance, despite its greater simplicity.
		A neo fuzzy neuron and its application to system identification and prediction of chaotic behavior.
	www.citebase.org /cgi-bin/citations?id=oai:arXiv.org:cs/0503078 (395 words)

	Example Fuzzy Expert System
		The problem this expert system addresses is supplemental feeding for range cows.
		The example is extremely simple and needs additional knowledge incorporated before it would be useful for developing actual range cow supplementation plans.
		However this example does demonstrate the mechanics of developing a fuzzy expert system.
	ag.arizona.edu /AREC/fuzzy/example.html (93 words)

	Expert System Course: Fuzzy Logic Expert System Design
		Study the basic principles in designing a frame-based expert system and use this understanding to develop a small frame-based system.
		Students are introduced to fuzzy logic programming techniques and learn how to implement a fuzzy logic expert system using a fuzzy logic development environment.
		They are also given the opportunity to demonstrate their understanding by building a fuzzy logic expert system that addresses a real-world problem.
	coel.ecgf.uakron.edu /durkin/fuzzy.htm (315 words)

	A Hierarchical Recurrent Neuro-Fuzzy System (ResearchIndex) (Site not responding. Last check: 2007-10-10)
		Abstract: Fuzzy systems, neural networks and its combination in neuro-fuzzy systems are already well established in data analysis and system control.
		Especially, neurofuzzy systems are well suited for the development of interactive data analysis tools, which enable the creation of rule-based knowledge from data and the introduction of a-priori knowledge into the process of data analysis.
		4 A Neuro-Fuzzy Synergism to Intelligent Systems (context) - Lin, Lee et al.
	citeseer.ist.psu.edu /451792.html (285 words)

	CONSTRUCTING FUZZY (Site not responding. Last check: 2007-10-10)
		Chapter 1: Fuzzy Mathematics: Fuzzy Logic, Fuzzy Sets, Fuzzy Numbers.
		Chapter 2: Defining Your System: Purpose, Conclusions to be Reached, Data.
		Chapter 6: Fuzzy Sets: Using Descriptive Words in Reasoning.
	members.aol.com /wsiler (211 words)

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