ABSTRACT
Electricity power supply company has entered the era of market economy as the deepening of reform, and the pressure to run the company well is increasing gradually. However, some questions, such as malicious default, electricity bills evasion, electricity cheat, and so on, still have not been solved. How to effectively avoid the arrearage risk and improve the economic benefit is key for the enterprises. This paper mainly studied the power users credit rating evaluation based on big data. This system proposed a new algorithm model which combined traditional k-Nearest-Neighbor (KNN) and Simulated annealing (SA) and used the big data software framework and data processing technology to rapid construct the users portrait as well as evaluate the users rating and credit rating division, evaluation and so on. Finally, the results were presented and then laid a good foundation for the researches in future.
2022-05-26 14:15:41
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升级版BP神经网络算法在电力企业财务风险预测中的模型与应用[外文翻译].doc
2022-05-26 09:10:38
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matlab 外文翻译 外文文献 英文文献 MATALAB 混合仿真平台控制算法的概述.doc
2022-05-25 14:08:20
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电子信息工程 测控技术与仪器 外文翻译 外文文献 英文文献 SJA1000 独立的CAN控制器应用指南
2022-05-24 20:52:49
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