Fault Diagnosis of Power Network Based on Artificial Bee Colony Algorithm
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摘要: 针对电网故障诊断中的0-1规划问题,从代数和几何角度优化了人工蜂群算法。仿真结果表明,人工蜂群算法具有可行性和合理性,并且综合性能显著优于传统的遗传算法;在两种人工蜂群算法中,基于几何思想的人工蜂群算法具有更好的稳定性和搜索能力,更加适用于对稳定性和精准度要求很高的场合。Abstract: In order to solve 0-1 programming problem in fault diagnosis of power network, the paper proposed optimization methods of artificial bee colony algorithm from aspects of algebra and geometry. The simulation results show that the artificial bee colony algorithm is feasible and reasonable, and the overall performance is significantly superior to traditional genetic algorithms; artificial bee colony algorithm based on geometric has better stability and search capabilities than the algorithm based on algebraic, and is more suitable for occasions with high stability and accuracy requirements.
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