电力公司与金融公司垂直联合学习架构及考虑用户信用评价的电价模型

Zhili Liu, Heyang Sun, Jinliang Song, Bin Zhang, Yuhang Yan, Bingbing Qiu, Lihang Jiang, Jingjing Li
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引用次数: 0

摘要

随着电力系统的发展,电力信用建设取得了积极的成效,但与政府和企业的要求相比还有一定的差距。本文提出了一个包含用户信用评价的垂直联合学习框架。通过在电力公司和金融公司之间构建垂直的联邦学习信用共享系统,降低了电力公司和金融公司之间的信息壁垒,降低了市场交易风险。通过构建基于用户信用评价的精细化电价定价模型,有利于降低用户成本,提高用户效率,鼓励用户高信用、高质量发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vertical Federated Learning Architecture for Power Company and Financial Company and Electricity Pricing Model Considering User Credit Evaluation
With the development of the electric power system, the construction of electric power credit has achieved positive results, but there is still a certain gap compared with the requirements of the government and enterprises. In this paper, a vertical federated learning framework including user credit evaluation is proposed. By constructing a vertical federated learning credit sharing system between electric power companies and financial companies, the information barriers of both are reduced and the market transaction risks are reduced. Through the construction of refined electricity price pricing model based on user credit evaluation, it is beneficial to reduce the cost and increase the efficiency of users, and encourage users to develop with high credit and high quality.
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