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针对特征选择问题的改进蚁群算法及其在电力系统安全评估中的应用

, PP. 154-160

Keywords: 特征选择,蚁群优化算法,k-近邻分类器,电力系统安全评估

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Abstract:

提出基于改进蚁群优化算法和k近邻算法相结合的特征选择算法。利用k近邻分类器的分类精度和特征子集维数加权构造了综合适应度指标,利用改进蚁群算法的全局寻优和多次优解搜索能力实现特征子集搜索。针对传统蚁群算法在特征选择中可能含有冗余特征的问题,设计了局部细化搜索方式,使得特征选择结果不含冗余特征的同时提高了算法的收敛性。通过测试数据验证了算法的有效性和快速性后,将所提算法应用于10机39节点电力系统的安全评估问题,获得了良好的特征选择和稳定预测性能。

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