Fuzzy Systems and Machine Intelligence Essay -- Artificial Intelligenc

foggy Systems and apparatus IntelligenceAbstract Our natural language is perhaps the most mesomorphic embodiment of communicating information for any given problem or situation. Combining natural language and numerical information into fuzzy establishments provides the modelling to represent knowledge, constraints and inference procedures. logy systems provide advantages in the development of systems solutions that suffice tasks much(prenominal) as automatic modeling, prediction, pattern recognition, and optimal decision making, manoeuver and planning. With this, fuzzy systems are an essential tool for industrial and manufacturing systems engineering. Fuzzy logic is a different approach to representing uncertainty - it emphasizes the double meanings of words in describing events - rather than the uncertainty about whether an event will occur, and allows decision-making under that uncertainty. Fuzzy logic attempts to capture the imperfect way we describe concepts, and works with them to form conclusions. The wonderful function about fuzzy logic is how you can impose everyday language to a problem. A descriptive sentence such as a little noisy, a lot of dirt, and deep spread over, can be decoded by a fuzzy logic system to perform various tasks based on the knowledge derived from the terms. An interesting thing about fuzzy logic is that it is always trying to work, and by tweaking the system, the coder is simply showing the system how to do a better job. The factor is still in control, but the fuzzy logic is mimicking how an operator would answer given the same situation. Introduction to the topic Fuzzy logic is a system analysis and modeling approach that allows an easier transition between colonial human thought processes and the ... ...sed to answer specific questions and provide definitions and examples of applications. Addresses are provided to those locations. The Fuzzy Logic Frequently Asked Questions Archive ht tp//www.uni-p assau.de/archive/faq/comp.answers/fuzzy-logic/ Brubaker, David I. Fuzzy Rules and Membership Functions from Data, Huntington practiced Brief, July 1993, No. 40. Cox, Earl. The Fuzzy Systems Handbook A Practitioners Guide to Building, Using, and Maintaining Fuzzy Systems. academic Press, New York, 1994. Kosko, Bart. Neural Networks and Fuzzy Systems. Prentice-Hall, Englewood Cliffs, 1992. Mcneill, Daniel, and Freiberger, Paul, Fuzzy Logic, Simon and Schuster, 1992. Zadeh, Lotfi A. Fuzzy Sets. Information & Control, Vol. 8, 1965, pp338-353. Zurada, Jacek M. hokey Neural Systems. West Publishing Co., New York, 1992.