By Hans-Paul Schwefel, Ingo Wegener, K.D. Weinert
The 30 coherently written chapters by way of prime researchers offered during this anthology are dedicated to easy effects completed in computational intelligence when you consider that 1997. The publication offers entire assurance of the center concerns within the box, in particular in fuzzy good judgment and regulate in addition to for evolutionary optimization algorithms together with genetic programming, in a finished and systematic manner. Theoretical and methodological investigations are complemented through prototypic functions for layout and administration initiatives in electric engineering, mechanical engineering, and chemical engineering.
This e-book becomes a worthy resource of reference for researchers lively in computational intelligence. complicated scholars and pros attracted to studying approximately and utilizing complicated innovations of computational intelligence will enjoy the e-book as an invaluable advisor more desirable by way of a number of examples and functions in numerous fields.
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Additional info for Advances in Computational Intelligence: Theory and Practice
On interpreting fuzzy ifthen rule bases by concepts of functional analysis. Technical Report CI-19/98, Collaborative Research Center 531, University of Dortmund, 1998. 44. J. Martin, J. Hiltner, M. Fathi, J. Statthaus, T. Hacklander, and B. Reusch. System for motion elimination in evaluation of renal function supported by vague knowledge. In Medical Imaging 2000, SPIE, San Diego, CA, February 2000. 45. J. M. Mendel. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice Hall, Englewood Cliffs, NJ, 2001.
M. Mizumoto and K. Tanaka. Some properties of fuzzy sets of type 2. Information and Control, 31(4):312-340, August 1976. 47. M. Mizumoto and K. Tanaka. Fuzzy sets under various operations. In 4th International Congress of Cybernetics and Systems, Amsterdam, The Netherlands, August 21-25, 1978. 48. C. -H. Temme. s-neural networks are fuzzy models. In 8th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2000), Madrid, July 3-7, 2000.
FATI-like similarity-based inference operators are possible, but the problem of aggregating rules is nontrivial without the intermediate representation in the form of a fuzzy relation. The investigations of similarity-based inference are ongoing. 6 Additional Remarks The presentation in the preceding subsections is a mere sketch of the most popular fuzzy inference methods. One goal of the research project reported here is to give a systematic and comprehensive account of the existing inference methods, their properties, possible equivalences, and conditions for the inference methods that will provide solutions for fuzzy IF-THEN rule bases.
Advances in Computational Intelligence: Theory and Practice by Hans-Paul Schwefel, Ingo Wegener, K.D. Weinert