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By Hans-Paul Schwefel, Ingo Wegener, K.D. Weinert

The 30 coherently written chapters via major researchers awarded during this anthology are dedicated to simple effects accomplished in computational intelligence on account that 1997. The publication offers whole insurance of the middle concerns within the box, particularly in fuzzy good judgment and regulate in addition to for evolutionary optimization algorithms together with genetic programming, in a complete and systematic method. Theoretical and methodological investigations are complemented by way of prototypic purposes for layout and administration initiatives in electric engineering, mechanical engineering, and chemical engineering.
This booklet turns into a priceless resource of reference for researchers energetic in computational intelligence. complex scholars and pros drawn to studying approximately and employing complicated options of computational intelligence will savor the publication as an invaluable consultant better through various examples and functions in a number of fields.

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D. Driankov, H. Hellendoorn, and M. Reinfrank. An Introduction to Fuzzy Control. Springer, Berlin, 1993. 7. D. Driankov, R. Palm, and H. Hellendoorn. Fuzzy control with fuzzy inputs: The need for new rule semantics. In FUZZ-IEEE '94 - Third IEEE International Conference on Fuzzy Systems, pages 13-21, Orlando, FL, June 26July 2, 1994. 8. D. Dubois, S. Lehmke, and H. Prade. A comparative study of logics of graded uncertainty and logics of graded truth. In S. Gottwald and E. P. Klement, editors, Linz '97 - Enriched Lattice Structures for Many- Valued and Fuzzy Logics, pages 10-15, Linz, Austria, February 25- March 1, 1997.

In the theory of classical crisp logical consequence operators, it is a fundamental and useful result that two consequence operators are identical if both agree on the empty set, are compact and monotone, and fulfill the inference and deduction properties. This also means that every operator fulfilling these properties is unique. Unfortunately, in the theory of fuzzy inference operators, the situation is much more complicated. The attempt to directly translate the results of classical logic to fuzzy inference yields some results, but they involve very strong conditions, and it is hard to estimate the applicability to real-world inference problems [100].

The main focus of this contribution is on determining an adequate compromise in this conflict area. The applicability of the concepts presented is demonstrated by means of complex real-world applications in the domains of power management control, classification in quality control, and prediction in financial service. 1 Introduction The use of fuzzy modeling is often motivated by the interpretability of the resulting model. A fuzzy model consists of qualitative IF-THEN rules that correspond to the way in which human knowledge is usually presented.

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