Customer Churn Prediction in Telecommunication Industry Using Data Mining Methods
Publish place: 6th National Conference on Applied Research in Computer Engineering and Information Technology
Publish Year: 1398
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CEPS06_086
تاریخ نمایه سازی: 9 اردیبهشت 1399
Abstract:
At present, in competitive space between companies and organizations, customers churn is their most important challenge. When a customer becomes churn, organizations lose one of their most important assets, which can lead to financial losses and even bankruptcy. Customer churn prediction using data mining techniques can alleviate these problems to some extent. The aim of the present study is to provide a hybrid method based on Genetic Algorithm and Modular Neural Network to customer churn prediction in telecommunication industries and use Irancell data as a sample.The accuracy result of this study which is 95.5% get the highest accuracy rank in comparisons with the result of other methods, which shows using modular neural network with two modules of feedforward neural network and also using genetic algorithm to obtain optimal structure for modules of the neural network are the most important indicators of this method to each the highest accuracy result among the rest of methods.
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Authors
Homa Meghyasi
Department of Management, Islamic Azad University, Tehran, Iran
Abas Rad
Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran