基于遗传算法和BP神经网络的电力客户信用评价模型  

Evaluation model of electricity customers credit based on genetic algorithm and BP neural network

作　　者：卢雯嘉 栗秋华[1,2] 周林[2] 李杨 冯克群 曾平 黄林 

机构地区：[1]重庆江北供电局,重庆401147 [2]重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆400044

出　　处：《电力需求侧管理》2009年第6期30-34,共5页Power Demand Side Management

基　　金：重庆市自然科学基金(2007BB6171)

摘　　要：对电力客户的信用进行分析评估对于供电企业将电力输送给可靠的电力用户、提高企业经济效益具有重要意义。在分析影响电力客户信用影响因素的基础上,构建了电力客户信用评价指标体系,将遗传算法和神经网络原理引入电力客户信用评价领域,提出了基于遗传算法和神经网络的电力客户信用评价模型。实证结果表明:模型具有较强的自组织、自学习和自适应能力,模型评估结果比较客观合理。If the power supply enterprises analyze and evaluate the credit of the electricity customers, they can transport the electricity to the reliable electricity customers. This will conduce to boost the economic benefit of the enterprises. Based on analyzing the factors which affect the credit of the electricity customers, we fabricate the credit evaluation index system to evaluate the credit of the electricity customers. This paper introduced the Genetic algorithm and Neural Network theory to the electricity customers Credit evaluation field. The credit evaluation model was built Up based On Genetic algorithm and Neural Network. Demonstration results indicated： the model had the strong ability of selforganization, self-study and self-adaptation. The evaluation result of the model was objective and reasonable.

关 键 词：供电企业 大电力客户 信用评估 遗传算法 神经网络 

分 类 号：F407.61[经济管理—产业经济]