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.
Conferences and Workshops on Fuzzy Systems: 1990-2001
From the Parallel and Distributed Processing Laboratory of the Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
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.
Japan Society for Fuzzy Theory and Systems (SOFT)
Established in 1989. SOFT has 1,670 individual members and 74 company members, publishes an official bimonthly journal and organizes fuzzy systems symposiums. There are 8 regional branches and 8 research groups in SOFT.
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.
Please mail questions/comments to the NAFIPS president (president@nafips.org) or to the NAFIPS web site maintainer (webmaster@nafips.org).
Spanish Association of Fuzzy Logic and Technologies
Promotes and disseminates the methods, techniques and developments of Fuzzy Logic and Technologies; Establish relations with other national or international Associations with similar aims; Organizes seminars and round tables on Fuzzy Logic and Technologies. Fuzzy Research Groups in Spain.
The European Society for Fuzzy Logic and Technology (EUSFLAT)
Established in 1998. The main goal of EUSFLAT are to represent the European fuzzy community of IFSA. To become a member of EUSFLAT please fill in the registration form.
Hungarian Fuzzy Society
Established in 1998. Honorary president: Tibor Vámos. President: Imre Rudas.
EUROFUSE Working Group on Fuzzy Sets of EURO
Established in 1975. The purpose of EUROFUSE is to communicate and promote the knowledge of the theory of fuzzy sets and related areas and their applications.
Roy, B. (1993). Decision science or decision-aid science? European journal of operational research , 66 (2), 184-203.
Waltz, David L. “Artificial Intelligence: Realizing the Ultimate Promises of Computing.” NEC Research Institute and the Computing Research Association (1996): 2 November 1999 .
Key Words; Artificial Intelligence, Multiple Intelligence, Fuzzy Logic, Fuzzy Logic Toolbox, Vocational Guidance, Decision Making
It has been thought in the near past that artificial intelligence would be a major threat to the human existence in this globe. But those days are no more. Now, this is being used for the betterment of the human lives that is to speed up the life. Algorithms are the factor behind it which has been made to help us connecting friends, finding information and even transporting us through the physical world.
While artificial intelligence can produce Ph.D. quality experts, a more difficult challenge lies in creating a naive observer. The common sense people use in everyday reasoning provides one of the most difficult challenges in building intelligent systems. Common sense reasoning is often based on incomplete knowledge and is powerfully broad in its use. Intelligent systems have historically been successful in specific domains with well defined structures. To make them succeed in a broad arena, they would need either a greater base of knowledge or be able to deal with uncertainty and learn. In light of the fact that the former option is more demanding in resources and assumes that all the appropriate knowledge is obtainable, the latter is an attr...
The neural network is required because of the information being scanned, traded, shipped and pulled from inventory by robots and tracking systems to report to the customer as quickly as possible. We have learned examples of AI being used today such as Expert Systems, Neural Networks, Genetic Algorithms, Intelligent Agents and Virtual
Norvig P. ARTIFICIAL INTELLIGENCE. New Scientist [serial online]. November 3, 2012;216(2889):i-8. Available from: Academic Search Complete, Ipswich, MA. Accessed January 20, 2014.
Through examples from several fields, this paper will describe the connections between Artificial Intelligence and other areas. Some of these areas make great contributions to AI research, others gain knowledge and technique from that same AI research. This paper will further detail the incredible capacity of AI research to be applied elsewhere to solve similar problems. The goal of this paper is to describe to the reader the impact that AI can create on seemingly unrelated fields.
The Passive Decision Support System, Active Decision Support System and Cooperative Decision Support System (2013). A Passive Decision Support System, is a system that assists in the process of decision making, however, it can’t bring out clear decisions (2013). An active Decision Support System, on the other hand, can bring out solutions and decision suggestions. The Cooperative Decision Support System allows the decision maker to change the decision suggestions provided by the system before the information is sent back to the system for validation (2013). While there are many ways computerized systems can be characterized, it is important to compare them in terms of what the user will be doing with the
4. Proceedings of the Second International Conference on Artificial Intelligence Applications on Wall Street, April 19-22 1993, New York City.
Finally almost a decade after the Dartmouth Conference, Centers for artificial intelligence research began to form at Carnegie Mellon and MIT. Further advancements were made in the field. The General Problem Solver (GPS) was developed based on the Wiener's feedback principle. The GPS was capable of solving a greater range of common sense problems.
In this paper Internal Model Control (IMC) & Fuzzy Controller is used for inverse response of boiler drum level. The Internal Model Control (IMC) philosophy relies on the Internal Model Principle, which states that control can be achieved only if the control system encapsulates, either implicitly or explicitly, some representation of the process to be
The Fuzzy Logic is a form of a systematic reasoning that can be integrated into automation systems with classical human reasoning schemes. Fuzzy theory was first suggested and probed by Prof Zadeh in 1965 [11] Fuzzy systems are apprehension based or rule based systems. The heart of a fuzzy system is a knowledge base inherent of the so-called If-Then rules. After allocating the fuzzy sets and their membership functions, rules must be noted to place an action to be taken for each combination of control variables. These rules will correlate the input and output variable by using IF-Then statements.
AIS can greatly contribute to managing Value Chain of any manufacturing company and resulting in
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...