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The credit evaluation model of electricity customer based on GA-PSO hybrid programming algorithm

机译:基于GA-PSO混合编程算法的电力客户信用评估模型

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Power supply enterprises face the business risk caused by electricity clients who break their promise on supply contracts. In order to avoid credit risk and conduct comprehensive evaluation on electricity clients, this paper builds an electricity client credit risk evaluation model based on GPSO hybrid algorithm, overcoming the shortcomings of traditional linear ECCR evaluation method. This new model integrates advantages of GA (genetic algorithm) and PSO, better than traditional multiple regression method and GP method regarding convergence performance and forecast accuracy. Simulation results indicate that hybrid model is simple and feasible, and it can improve efficiency and accuracy of evaluation.
机译:供电企业面临由违反供应合同承诺的电力客户造成的业务风险。为了避免信用风险并对电力客户进行全面评估,本文建立了基于GPSO混合算法的电力客户信用风险评估模型,克服了传统线性ECCR评价方法的缺点。这种新模型集成了GA(遗传算法)和PSO的优点,优于传统的多元回归方法和关于收敛性能和预测准确性的GP方法。仿真结果表明,混合模型简单可行,可以提高评估的效率和准确性。

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