Application of big data method in forecasting potential sensitive customers of electric power
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 applicati...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2019-11-01
|
| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019271/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841530571662032896 |
|---|---|
| author | Xiaofeng CHEN Yadi ZHAO Lipeng ZHANG Feng ZHU |
| author_facet | Xiaofeng CHEN Yadi ZHAO Lipeng ZHANG Feng ZHU |
| author_sort | Xiaofeng CHEN |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-166f4f0741344ba6a687e3e39c9b6cf6 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2019-11-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-166f4f0741344ba6a687e3e39c9b6cf62025-01-15T03:02:05ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012019-11-013511712459586179Application of big data method in forecasting potential sensitive customers of electric powerXiaofeng CHENYadi ZHAOLipeng ZHANGFeng ZHUWith 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.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019271/complaint work orderdata miningentropy weight methoddecision tree |
| spellingShingle | Xiaofeng CHEN Yadi ZHAO Lipeng ZHANG Feng ZHU Application of big data method in forecasting potential sensitive customers of electric power Dianxin kexue complaint work order data mining entropy weight method decision tree |
| title | Application of big data method in forecasting potential sensitive customers of electric power |
| title_full | Application of big data method in forecasting potential sensitive customers of electric power |
| title_fullStr | Application of big data method in forecasting potential sensitive customers of electric power |
| title_full_unstemmed | Application of big data method in forecasting potential sensitive customers of electric power |
| title_short | Application of big data method in forecasting potential sensitive customers of electric power |
| title_sort | application of big data method in forecasting potential sensitive customers of electric power |
| topic | complaint work order data mining entropy weight method decision tree |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019271/ |
| work_keys_str_mv | AT xiaofengchen applicationofbigdatamethodinforecastingpotentialsensitivecustomersofelectricpower AT yadizhao applicationofbigdatamethodinforecastingpotentialsensitivecustomersofelectricpower AT lipengzhang applicationofbigdatamethodinforecastingpotentialsensitivecustomersofelectricpower AT fengzhu applicationofbigdatamethodinforecastingpotentialsensitivecustomersofelectricpower |