Deep Convolutional Neural Network Based Churn Prediction for Telecommunication Industry-Reference-Cited by-同舟云学术

Deep Convolutional Neural Network Based Churn Prediction for Telecommunication Industry

Published:2022 Issue:3 Volume:43 Page:1255-1270
ISSN:0267-6192
Container-title:Computer Systems Science and Engineering
language:en
Short-container-title:

Author:

Almufadi Naseebah,Mustafa Qamar Ali

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.techscience.com/csse/v43n3/47701/pdf

Reference21 articles.

1. C. H. Lovelock, P. Patterson and J. Wirtz, “Services marketing: An Asia-pacific and Australian perspective,” 6th ed., Melbourne, Vic, Australia: Pearson, 2015. [Online]. Available: https://www.amazon.com/Services-Marketing-Asia-Pacific-Australian-Perspective/dp/B07FM442C1.

2. Customer churn prediction in the online new media platform: A case study on juzi entertainment;Yuan,2017

3. Evaluating deep learning in chum prediction for everything-as-a-service in the cloud;Sung,2017

4. Deep learning of representations: looking forward;Bengio,2013

5. High accuracy predictive modelling for customer churn prediction in telecom industry;Prashanth,2017

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Risk assessment of customer churn in telco using FCLCNN-LSTM model;Expert Systems with Applications;2024-08

2. Comparative Study of Bank Customers Churn Prediction using AI/ML;2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT);2024-04-06

3. Customer Churn Prediction Using Tunicate Swarm Optimization Based Hybrid Machine Learning Algorithms;2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT);2024-03-15

4. Tri-Strategy Remora Optimization Algorithm based Support Vector Machine for Customer Churn Prediction;2024 International Conference on Integrated Circuits and Communication Systems (ICICACS);2024-02-23

5. Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature;IEEE Access;2024