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Download e-book for kindle: Evolutionary Computation by Wellington Pinheiro dos Santos (editor)

By Wellington Pinheiro dos Santos (editor)

ISBN-10: 9533070080

ISBN-13: 9789533070087

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Interactive Genetic Algorithms with Individual’s Uncertain Fitness 43 7. Acknowledgements This work was completed when Dun-wei Gong was visiting CERCIA, School of Computer Science, the University of Birmingham. It was jointly supported by NSFC with granted No. 60775044 and Program for New Century Excellent Talents in University with granted No. NCET-07-0802. 8. G. W. (1996). Neural network fitness functions for a musical IGA, Proceedings of International Symposium on Intelligent Industrial Automation and Soft Computing, pp.

First, we adopt a novel expression of an individual’s fitness, which much accords with the user’s fuzzy cognitive on the evaluated object. Second, we present an effective method to compare different individuals when an individual’s fitness is expressed with a fuzzy number, which is necessary for a population to evolve. These contributions can improve the performance of existing IGAs in alleviating user fatigue and looking for the optimal solutions of an optimization problem, therefore it is beneficial to solve complicated problems with implicit or fuzzy indices.

F(x) ( f ) 1 α0 α fα (xi ) c( xi ) fα (xj ) f (x ) c( x j ) α i fα (x j ) Fig. 5. Two individuals’ fitness on condition of c(xi ) < c(x j ) and f α ≤α0 . 3 to select the dominant individual in tournament selection. It is easy to observe from the process of comparison between xi and x j that what determines an individual to be the dominant one in tournament selection is p(xi , xj ) and p(xi , x j ) . For case 2 both dominance probabilities have close relation with α -cut set. Even if we have the same fuzzy set, different α will lead to different α -cut sets.

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Evolutionary Computation by Wellington Pinheiro dos Santos (editor)


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