An integrated method based on hesitant fuzzy theory and RFM model to insurance customers’ segmentation and lifetime value determination-Reference-Cited by-同舟云学术

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An integrated method based on hesitant fuzzy theory and RFM model to insurance customers’ segmentation and lifetime value determination

Published:2018-07-27 Issue:1 Volume:35 Page:159-169
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Yan Chun¹,Sun Haitang¹,Liu Wei²³,Chen Jin²

Affiliation:

1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Shandong, Qingdao, China

2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

3. Shandong Province Key Laboratory of Wisdom Mine Information Technology, Shandong University of Science and Technology, Qingdao, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference28 articles.

1. Yan C. , Wang L. , Liu W. and M. Qi , Financial early warning ofnon-life insurance company based on RBF neural networkoptimized bygenetic algorithm, Concurrency and Computation: Practice and Experience(2017) DOI: 10.1002/cpe.4343

2. Li Y.Q. , Yan C. , Liu W. and M.Z. Li , A principle componentanalysis-based random forest with the potential nearest neighbormethod for automobile insurance fraud identification, Applied Soft Computing(2017) doi: 10.1016/j.asoc.2017.07.027 .

3. Study of fuzzy association rules andcross-selling toward property insurance customers based on FARMA;Yan;Journal of Intelligent & Fuzzy Systems,2016

4. Application of customer lifetime valuemodel in make-to-order manufacturing;Tukel;Journal of Business &Industrial Marketing,2013

5. Customer equity andCLV in Spanish telecommunication services;Segarra-Moliner;Journal of Business Research,2016

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1. Prediction and Optimization of Life Insurance Prediction Based on FEA and ANN Hybrid Approach;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02

2. RFM Model and K-Means Clustering Analysis of Transit Traveller Profiles: A Case Study;Journal of Advanced Transportation;2022-08-08

3. Analysing the nexus between artificial neural networks and ARIMA models in predicting customer lifetime value (CLV) for complex development of society and industrial activities;Industria Textila;2022-07-01

4. Evolutionary multi-objective customer segmentation approach based on descriptive and predictive behaviour of customers: application to the banking sector;Journal of Experimental & Theoretical Artificial Intelligence;2022-05-31

5. Evaluation and Selection of Insurance Marketing Schemes Driven by Multisource Big Data;Mathematical Problems in Engineering;2022-04-22

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