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针对多簇支持向量机参数设置缺乏科学依据、参数选取随意性较大的问题,利用布谷鸟搜索算法对其进行了改进,并应用改进的多簇支持向量机对装甲装备技术状况进行了评估,最后与粒子群优化算法、遗传算法改进的多簇支持向量机评估结果进行了对比分析,验证了该方法在装甲装备技术状况评估中的可行性与合理性。
Aiming at the lack of scientific basis and parameter selection of multi-cluster support vector machine, the cumber search algorithm is used to improve it. The improved multi-cluster support vector machine is used to evaluate the technical condition of armored equipment. Finally, the results of PSO-SVM and GA-SVM are compared and analyzed, and the feasibility and rationality of this method in the assessment of technical status of armored equipment are verified.