By Japan) International Conference on Soft Computing 1998 (Iizuka-Shi
Smooth computing (SC) comprises a number of computing paradigms, together with neural networks, fuzzy set conception, approximate reasoning, and derivative-free optimization tools equivalent to genetic algorithms. the mixing of these constituent methodologies types the middle of SC. additionally, the synergy permits SC to include human wisdom successfully, take care of imprecision and uncertainty, and discover ways to adapt to unknown or altering environments for larger functionality. including different sleek applied sciences, SC and its functions exert unparalleled impression on clever structures that mimic human intelligence in considering, studying, reasoning, and plenty of different elements. wisdom engineering (KE), which offers with wisdom acquisition, illustration, validation, inferencing, rationalization and upkeep, has made major development lately, as a result of the indefatigable efforts of researchers. surely, the new themes of information mining and knowledge/data discovery have injected new lifestyles into the classical AI global. This e-book tells readers how KE has been encouraged and prolonged by way of SC and the way SC might be precious in pushing the frontier of KE additional. it's meant for researchers and graduate scholars to exploit as a reference within the research of information engineering and clever structures. The reader is predicted to have a easy wisdom of fuzzy good judgment, neural networks, genetic algorithms and knowledge-based structures.
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Additional info for A New Paradigm of Knowledge Engineering by Soft Computing (Fuzzy Logic Systems Institute (Flsi) Soft Computing Series, Volume 5)
Part I: Fuzzy Knowledge-Based Systems Chapter 2 Linguistic Integrity: A Framework for Fuzzy Modeling -AFRELI Algorithm Jairo Espinosa, Joos Vandewalle Katholieke Universiteit Leuven Abstract In this paper, a method for fuzzy modeling is presented. The framework of the method is the concept of Linguistic Integrity. The use of this framework present several advantages. The most important is transparency, this transparency can be exploited in two directions. T h e first direction is in data mining where the method can provide a linguistic relation (IF-THEN rules) among the variables.
So, the membership functions should be clearly different. Too much overlap among two membership functions means that they are representing the same linguistic concept. The assumption of the overlap equal to | makes sure that the support of each fuzzy set will be different. The distance between the modal values of the membership functions is also very important to make sure that the membership functions can be distinguished. ,N (2) — Justifiable Number of Elements The number of sets should be compatible with the number of "quantifiers" that a human being can handle.
The user 48 H. Ohno & T. Furuhashi interacts with the computer system for knowledge acquisition through the degree of explanation. If the constraints are not satisfied during the operation of EP, the parameter of the membership functions, that is included in a solution vector of EP, are initialized and the EP operation is continued. The solutions of EP are real-valued vectors corresponding to the unknown parameters of the fuzzy system and the adaptable standard deviations that determine the step size for each unknown parameter.
A New Paradigm of Knowledge Engineering by Soft Computing (Fuzzy Logic Systems Institute (Flsi) Soft Computing Series, Volume 5) by Japan) International Conference on Soft Computing 1998 (Iizuka-Shi