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2篇 您的检索式：作者名="Guo Guangsong"

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		题名	作者	年代	出处	被引量
	1	Adaptive interactive genetic algorithms with individual interval fitness显示文摘It is necessary to enhance the performance of interactive genetic algorithms in order to apply them to complicated optimization prob- lems successfully. An adaptive interactive genetic algorithm with individual interval fitness is proposed in this paper in which an indi- vidual fitness is expressed by an interval. Through analyzing the fitness, information reflecting the distribution of an evolutionary population is picked up, namely, the difference of evaluating superior individuals and the difference of evaluating a population. Based on these, the adaptive probabilities of crossover and mutation operators of an individual are presented. The algorithm proposed in this paper is applied to a fashion evolutionary design system, and the results show that it can find many satisfactory solutions per generation. The achievement of the paper provides a new approach to enhance the performance of interactive genetic algorithms.	Dunwei Gong Guangsong Guo Li Lu Hongmei Ma	2008	Progress in Natural Science:Materials International2008，18，3：	13
	2	Interactive Genetic Algorithms with Interval Fitness of Evolutionary Individuals显示文摘	Gong Dunwei Guo Guangsong	2007	Dynamics of Continuous Discrete and Impulsive Systems2007，14，2：	1

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