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Combat effectiveness evaluation method of photoelectric defense system based on SVM optimized by particle swarm algorithm

机译:基于粒子群算法的基于支持向量机的光电防御系统作战效能评估方法

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The combat effectiveness is an important indicator of the photoelectric defense system quality. When used in combat, the influence factors of the combat effectiveness are complex and show a nonlinear relationship. This paper proposes to apply the SVM to combat effectiveness evaluation, propose the thought of making the photoelectric defense system combat effectiveness value to different “classification”. For the problem of the structure of SVM is difficult to determine, this paper puts forward to optimize the structure of SVM by the particle swarm algorithm. The example verifies the validity of the methods above, which overcome the weakness of the expert decision-making system not easy to modify and the poor quality of the adaptive ability.
机译:战斗力是光电防御系统质量的重要指标。当用于战斗时,战斗力的影响因素是复杂的,并显示出非线性关系。本文提出将支持向量机应用于作战效能评估,提出使光电防御系统作战效能值适应不同“分类”的思想。针对支持向量机结构难以确定的问题,提出了利用粒子群算法对支持向量机的结构进行优化。实例验证了上述方法的有效性,克服了专家决策系统不易修改,适应能力差的缺点。

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