Research on a complaint prediction model utilizing joint neural networks

Xiaoliang MA; Ying LIU; Jie GAO

doi:10.11959/j.issn.1000-0801.2024006

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Research on a complaint prediction model utilizing joint neural networks

Research and Development | 更新时间：2024-06-05

- Research on a complaint prediction model utilizing joint neural networks
- Telecommunications Science Vol. 40, Issue 1, Pages: 48-58(2024)
- 作者机构：
  
  1. 西安电子科技大学，陕西西安 710071
  2. 中国电信股份有限公司广州分公司，广东广州 510620
  3. 马晓亮劳模与工匠人才创新工作室，广东广州 510620
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2024006
  CLC： TP393
- Published Online：2024-01，
  
  Published：20 January 2024
- 稿件说明：
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Xiaoliang MA, Ying LIU, Jie GAO. Research on a complaint prediction model utilizing joint neural networks[J]. Telecommunications science, 2024, 40(1): 48-58.
DOI：

Xiaoliang MA, Ying LIU, Jie GAO. Research on a complaint prediction model utilizing joint neural networks[J]. Telecommunications science, 2024, 40(1): 48-58. DOI： 10.11959/j.issn.1000-0801.2024006.

摘要

对影响电信运营商重复投诉的关键因素进行深入探讨，旨在提高服务质量并构建风险预测模型。基于运营商客服数据，研究采用了 Logistic 回归、BP 神经网络以及二者联合建模的方法。Logistic 回归模型确定了5个主要影响因素，预测重复投诉发生的概率，精度达到 80.0%。BP 神经网络则选取了 81个影响因素，预测精度为 90.6%。在此基础上，构建了联合模型，其精度高达 92.8%。实际应用于某省会电信运营商后，重复投诉率下降了3.2%，成效显著，为提高电信运营商服务质量、降低重复投诉率提供了有力支持，对我国电信行业发展具有重要意义。

Abstract

By conducting in-depth exploration on the key factors affecting repeat complaints of telecom operators

this study aimed to improve service quality and construct a risk prediction model.Based on the operator’s customer service data

the study employed Logistic regression

BP neural network

and their combined modeling methods.The Logistic regression model identified five major influencing factors

predicting the probability of repeat complaints with an accuracy of 80.0%.The BP neural network selected 81 influencing factors

achieving a prediction accuracy of 90.6%.On this basis

a combined model was constructed with an accuracy rate of up to 92.8%.After practical application in a provincial telecom operator

the repeat complaint rate decreased by 3.2%

demonstrating a significant impact.Strong support is provided for improving the service quality of telecom operators and reducing repeat complaints

which is of great significance for the development of the telecom industry in China.

关键词

Keywords

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