Providing an intelligent management system for allocating telecommunications system facilities to predict customer churn based on artificial neural networks and the evolutionary algorithm of smart droplets

Document Type : Original Article

Authors
Maedeh Rahmani 1
Farshid Vazifehdoost 2
Mehdi Razapoor Mirsaleh 3
1 Payam Noor University Kish International Center
2 Payam Noor University, Qeshm International Center
3 Assistant Professor, Department of Computer Engineering and Information Technology, Payam Noor University
Abstract
In the telecommunications industry, a large volume of data is generated by a large number of customers on a daily basis, and acquiring a new customer base is more costly than retaining existing customers, and effective customer analysis is very important to achieve business prosperity. Therefore, in this study, an intelligent model for allocating telecommunications system resources to predict customer churn based on artificial neural networks and the evolutionary algorithm of intelligent droplets was presented, in order to make informed business decisions that increase revenue and improve customer satisfaction. The aim of this study is to investigate how consumer predictions change based on machine learning classification algorithms. This method is able to select the best machine learning classifier for the consumer dataset under analysis. The role of the artificial neural network based on the intelligent water algorithm in this model is to perform an extensive analysis of consumer patterns using the classifier. In simulation, the proposed model has better results than other methods in various criteria.
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