6th International Conference on Electronics, Communication and Aerospace Technology (ICECA 2022)

2 / 2022-10-23 18:13:48

A SURVEY ON ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION FOR CHURN PREDICTION

Churn in Telecom, Data Mining, Classification, Supervised Learning, Artificial Neural Networks, Machine Learning.

One of the most significant issues in the telecom industry is jumping of customer to another network called customer churn. It has a direct impact on the revenue of the business, particularly in the telecom sector. As a result, businesses are attempting to develop strategies for anticipating customer turnover. Therefore, it is crucial to identify the factors that influence customer churn. Our paper demonstrates how to identify customer attrition effectively in the telecom sector. Our article includes a churn ANN model, which helps telecom businesses manage the individuals who are willing to churn, as well as some practical data analysis, which can be used to draw conclusions from the data. This prediction model with a high accuracy score can be created using neural networks, machine learning algorithms, artificial intelligence and other technologies.One of the most significant issues in the telecom industry is jumping of customer to another network called customer churn. It has a direct impact on the revenue of the business, particularly in the telecom sector. As a result, businesses are attempting to develop strategies for anticipating customer turnover. Therefore, it is crucial to identify the factors that influence customer churn. Our paper demonstrates how to identify customer attrition effectively in the telecom sector. Our article includes a churn ANN model, which helps telecom businesses manage the individuals who are willing to churn, as well as some practical data analysis, which can be used to draw conclusions from the data. This prediction model with a high accuracy score can be created using neural networks, machine learning algorithms, artificial intelligence and other technologies.