A new method for character optimization based on modified genetic algorithm in multiple sources information fusion

A new method based on modified genetic algorithm for character optimization in multiple sources information fusion is proposed in this papers which, uses problem-specific genetic algorithms for character optimizing instead of the standard genetic algorithms. The proposed method based on genetic algorithm incorporates the domain knowledge into its specialized operators, where some also combine a local search technique in the multiple sources information fusion. The effectiveness and efficiency of the proposed genetic algorithm, is demonstrated by simulation studies. The irreplaceable role of the specialized genetic operators in the proposed GA for solving character optimization, problem of multiple sources information fusion is demonstrated by a comparison study. The experiment results indicate that the optimizing characteristic method in this article is valid, can improve the data Correct classification.