基于鱼群算法优化BP神经网络的电力客户满意度综合评价方法Comprehensive Evaluation of Electric Power Customer Satisfaction Based on BP Neural Network Optimized by Fish Swarm Algorithm
杨淑霞;韩奇;徐琳茜;路石俊;
摘要(Abstract):
首先从形象、期望、对供电质量的感知、对服务质量的感知、价值感知、抱怨、忠诚7个方面建立供电客户满意度测评指标体系,然后分析了BP神经网络与鱼群算法结合的可行性,探讨了鱼群算法优化神经网络的步骤。最后对5个地区2009年供电客户满意度测评数据,在专家打分测评的基础上,运用神经网络及鱼群算法优化神经网络方法进行满意度评价。前者在收敛过程中130次停留在误差值10-1左右,后者在局部最优处仅仅停留10次;在误差值为0.001时,前者经过168次训练后能够达到目标,而后者只需要88次训练就能达到目标。结果表明鱼群算法优化神经网络具有准确、快捷、简易等优点,此方法用于供电客户满意度评价行之有效。
关键词(KeyWords): 鱼群算法;BP神经网络;电力客户满意度;综合评价
基金项目(Foundation):
作者(Author): 杨淑霞;韩奇;徐琳茜;路石俊;
Email:
DOI: 10.13335/j.1000-3673.pst.2011.05.020
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