关键词: 遗传算法, 粗糙集, 属性约简, 全局寻优, 适应度函数

Abstract: Aiming at the lower generalization ability and high false rate of the present pattern recognition algorithms with fixed flame image characteristic,the algorithm of adaptive selection flame image features is proposed in this paper.According to the two basic principles of characteristic reduction,genetic optimization is introduced into the attributes reduction of Rough Set(RS).The ratios of crossover and mutation are changed with individual’s fitness to protect good individual and eliminate bad individual.It dynamically clips the similar individuals and adds new individual,increases the diversity of population to improve the global optimization ability of Genetic Algorithm (GA).Experimental results show that the algorithm can reduce the dimension of feature space,and the average recognition rate of the flame is increased by 16% compared with the image fire detection algorithm based on Support Vector Machine(SVM).

Key words: Genetic Algorithm(GA), Rough Set(RS), attribute reduction, global optimization, fitness function