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.
全文待审
Anila A / Sri Eshwar College Of Engineering
Prakash U / Sri Eshwar College Of Engineering
Kavinayaa N / Sri Eshwar College Of Engineering
Swetha C / Sri Eshwar College Of Engineering
Vigneshwaran K / Sri Eshwar College Of Engineering
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.
重要日期
  • 会议日期

    12月01日

    2022

    12月03日

    2022

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