Application of big data method in forecasting potential sensitive customers of electric power

Xiaofeng CHEN; Yadi ZHAO; Lipeng ZHANG; Feng ZHU

doi:10.11959/j.issn.1000-0801.2019271

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Application of big data method in forecasting potential sensitive customers of electric power

Power informatization column | 更新时间：2024-06-05

- Application of big data method in forecasting potential sensitive customers of electric power
- Telecommunications Science Vol. 35, Issue 11, Pages: 117-124(2019)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2019271
  CLC： TP393
- Published Online：2019-11，
  
  Published：20 November 2019
- 稿件说明：
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Xiaofeng CHEN, Yadi ZHAO, Lipeng ZHANG, et al. Application of big data method in forecasting potential sensitive customers of electric power[J]. Telecommunications science, 2019, 35(11): 117-124.
DOI：

Xiaofeng CHEN, Yadi ZHAO, Lipeng ZHANG, et al. Application of big data method in forecasting potential sensitive customers of electric power[J]. Telecommunications science, 2019, 35(11): 117-124. DOI： 10.11959/j.issn.1000-0801.2019271.

摘要

随着 95598 业务的不断发展延伸，人工话务强度增大。为了进一步加深对客户隐性特征以及诉求的认识和理解，提升 95598 人工精细化客户服务水平，对投诉倾向等客户服务中的典型应用场景进行了需求细化。基于电力服务工单数据，选取建模关键指标，通过熵权法、主成分分析和决策树等数据挖掘算法，对潜在投诉倾向客户和计划停电敏感客户进行识别，以便有针对性地进行服务资源调度，充分做好应对措施，有效减少投诉压力，提升服务精度。

Abstract

With the continuous development and extension of 95598 business

the intensity of manual telephone traffic increases.In order to further deepen the consciousness and understanding of the hidden features and the demands of the customers

improve the customer service level of 95598

the typical application scenarios in the customer service such as the tendency of the complaint were refined.Based on the data of power service orders

the key index of modeling was selected.Through entropy weight method

principal component analysis and decision tree and other data mining algorithms

potential complaint propensity customers and planned blackout sensitive customers in order to carry out targeted service resource scheduling were identified

fully do a good job of response measures

effectively reduce complaint pressure and improve service accuracy.

关键词

Keywords

references

张哲 . 电力市场营销与优质服务的作用 [J ] . 企业技术开发 , 2016 ( 5 ): 115 - 116 .

ZHENG Z . The role of electric marketing and high quality [J ] . Technological Development of Enterprise , 2016 ( 5 ): 115 - 116 .

刘容宇 . 探讨供电企业电力营销的现状及其优质服务策略 [J ] . 通讯世界 , 2014 ( 17 ): 82 - 83 .

LIU R Y . Discussion on the present situation of power marketing in power supply enterprises and its high quality service strategy [J ] . Communication World , 2014 ( 17 ): 82 - 83 .

庄雪霞 . 现代供电企业电力营销优质服务策略提升分析 [J ] . 中国高新技术企业 , 2013 ( 14 ): 141 - 142 .

ZHUANG X X . Analysis on the promotion of high quality service strategy of electric power marketing in modern power supply enterprises [J ] . China High-Tech Enterprises , 2013 ( 14 ): 141 - 142 .

陈丽钕 . 剖析电力企业营销服务管理的总体策略 [J ] . 大科技 , 2012 ( 23 ): 185 - 186 .

CHEN L N . Analysis of the overall strategy of marketing service management in electric power enterprises [J ] . Super Science , 2012 ( 23 ): 185 - 186 .

邹保 , 周亮 . 电网企业数据服务研究 [J ] . 电力信息与通信技术 , 2010 ( 9 ): 30 - 32 .

ZOU B , ZHOU L . Research on data service of power grid enterprises [J ] . Electric Power Information and Communication Technology , 2010 ( 9 ): 30 - 32 .

鞠小丽 . 基于数据仓库技术的电力营销分析系统 [J ] . 数字技术与应用 , 2012 ( 3 ): 68 - 69 .

JU X L . Power marketing analysis system based on data warehouse technology [J ] . Digital Technology and Application , 2012 ( 3 ): 68 - 69 .

杨华飞 , 李栋华 , 程明 . 电力大数据关键技术及建设思路的分析和研究 [J ] . 电力信息与通信技术 , 2015 , 13 ( 1 ): 7 - 10 . http://www.dlxxtx.com/CN/abstract/abstract596.shtml http://www.dlxxtx.com/CN/abstract/abstract596.shtml

YANG H F , LI D H , CHENG M . Analysis and research on key technologies and construction ideas of electric power big data [J ] . Electric Power Information and Communication Technology , 2015 , 13 ( 1 ): 7 - 10 .

赵会敏 , 雒江涛 , 杨军超 , 等 . 集成BP神经网络预测模型的研究与应用 [J ] . 电信科学 , 2016 , 32 ( 2 ): 60 - 67 .

ZHAO H M , LUO J T , YANG J C , et al . Research and application of prediction model based on ensemble BP neural network [J ] . Telecommunications Science , 2016 , 32 ( 2 ): 60 - 67 .

严宇平 , 吴广财 . 基于数据挖掘技术的客户停电敏感度研究与应用 [J ] . 新技术新工艺 , 2015 ( 9 ): 89 - 93 .

YAN Y P , WU G C . Research and application of customer blackout sensitivity based on data mining technology [J ] . New Technology ＆ New Process , 2015 ( 9 ): 89 - 93 .

赵会茹 , 霍慧娟 , 李春杰 . 基于因子分析和Logistic回归模型的电力普遍服务受助个体主客观诉求影响因素分析 [J ] . 陕西电力 , 2014 , 42 ( 8 ): 65 - 71 .

ZHAO H R , HUO H J , LI C J . Analysis on the influencing factors of subjective and objective demands of power universal service recipients based on factor analysis and logistic regression model [J ] . Shanxi Electric Power , 2014 , 42 ( 8 ): 65 - 71 .

STEVEN B , EWAN K , EDWARD L . Python自然语言处理 [M ] . 北京 : 人民邮电出版社 , 2014 .

STEVEN B , EWAN K , EDWARD L . Python natural language processing [M ] . Beijing : Posts ＆ Telecom PressPress , 2014 .

吴刚勇 , 张千斌 , 吴恒超 , 等 . 基于自然语言处理技术的电力客户投诉工单文本挖掘分析 [J ] . 电力大数据 , 2018 ( 10 ): 68 - 73 .

WU G Y , ZHANG Q B , WU H C , et al . Text mining analysis of power customer complaints based on natural language processing technology [J ] . Power Systems and Big Data , 2018 ( 10 ): 68 - 73 .

邹云峰 , 何维民 , 赵洪莹 , 等 . 文本挖掘技术在电力工单数据分析中的应用 [J ] . 现代电子技术 , 2016 , 39 ( 17 ): 149 - 152 .

ZOU Y F , HE W M , ZHAO H Y , et al . Application of text mining technology in power work order data analysis [J ] . Modern Electronics Technique , 2016 , 39 ( 17 ): 149 - 152 .

REZAC M . Measuring quality of scoring models using information value [J ] . Journal of Communication and Computer , 2011 ( 3 ): 234 - 239 . DOI: 10.1097/PRS.0000000000003430 http://doi.org/10.1097/PRS.0000000000003430 https://www.ncbi.nlm.nih.gov/pubmed/28654621 https://www.ncbi.nlm.nih.gov/pubmed/28654621

刘荣 , 冯国生 , 丁维岱 . SAS 统计分析与应用 [M ] . 北京 : 机械工业出版社 , 2011 .

LIU R , FENG G S , DING W D . Statistical analysis and application of SAS [M ] . Beijing : China Machine PressPress , 2011 .

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