一种多源信息的最优融合方法研究

Research on an Optimal Fusion Method of Multi-source Information

  • 摘要: 针对目前多源信息融合存在的问题,本文模拟人类思维机制,尝试将粗集和支持向量机两者结合起来,利用粗集理论的强定性分析能力以及支持向量机的快速联想能力对多源信息进行融合.引入了遗传算法,借助其优越的全局最优搜索能力来进行融合的优化.实例研究结果表明,该方法具有良好的容错性、鲁棒性和准确性.

     

    Abstract: Aiming at the existing problems of multi-source information fusion, a method which simulates human thinking mechanism is presented.-In this method, rough sets theory and support vector machines are combined together, and by the aid of the strong qualitative analysis ability of rough sets theory and the quick association ability of support vector machines, multi-source information are fused. Genetic algorithm is introduced because of its excellent global optimization ability, and fused results are optimized. The results show that the proposed method has good abilities of-fault-tolerance, robustness and accuracy.

     

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