| 王林信,余向前,欧阳燕,陈元楷,张晓庆.基于长短期记忆网络的电费回收风险分析方法[J].电力需求侧管理,2023,25(1):104-109 |
| 基于长短期记忆网络的电费回收风险分析方法 |
| Risk analysis of electricity tariff recovery based on long-and-short term memory network |
| 投稿时间：2022-09-02 修订日期：2022-11-30 |
| DOI：10.3969/j.issn.1009-1831.2023.01.017 |
| 中文关键词: 电费回收 风险分析 长短期记忆网络 信用评估 AP聚类 |
| 英文关键词: electricity tariff recovery risk analysis long term and short term memory network credit evaluation AP clustering |
| 基金项目:国网甘肃省电力公司科技项目(LH18L498-S ) |
|
| 摘要点击次数: 690 |
| 全文下载次数: 266 |
| 中文摘要: |
| 新冠疫情在全世界的蔓延，对国内的经济发展造成了较大的影响，供电企业电费回收压力日益增大。针对新冠疫情形势下电费回收风险分析准确性差、催费针对性不强的问题，提出了一种基于长短期记忆网络的电费风险分析方法。首先，建立供电用户分类体系，通过AP聚类，实现对供电用户的分级分类；其次，通过供电用户征信、司法裁判等信息综合对供电用户的信用进行评估；再次，通过长短期记忆网络，结合用户的历史的缴费信息和用户信用进行电费回收分析，预测可能存在的欠费风险。最后，在某地区供电公司进行实例运行，其运行结果验证了所提方法的可行性和有效性。 |
| 英文摘要: |
| With the spread of COVID-19 in the whole world,the domestic economic development has been greatly affected, and the pressure of power supply company’s electricity recovery has been increasing. In order to solve the problem of poor accuracy of electricity charge recovery and less pertinence in the situation of COVID- 19, a risk analysis method based on long term and short term memory network is proposed. Firstly, the classification system of power supply users is established, and the classification of power supply users is realized by AP clustering. Secondly, the credit of power supply users is evaluated through the information of power supply users’credit investigation and judicial judgment. Thirdly,through the long-term and short-term memory network, combined with the user’s historical payment information and the user’s credit, the electricity charge recovery analysis is carried out, and the possible arrears risk is predicted. Finally, an example is run in a regional power supply company, and the results verify the feasibility and effectiveness of the proposed method. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |