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  • Open Access


    Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-CatBoost

    Yaling Xu, Congjun Rao*, Xinping Xiao, Fuyan Hu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2715-2742, 2023, DOI:10.32604/cmes.2023.029023

    Abstract As the banking industry gradually steps into the digital era of Bank 4.0, business competition is becoming increasingly fierce, and banks are also facing the problem of massive customer churn. To better maintain their customer resources, it is crucial for banks to accurately predict customers with a tendency to churn. Aiming at the typical binary classification problem like customer churn, this paper establishes an early-warning model for credit card customer churn. That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm (GSA) and an Improved Beetle Antennae Search (IBAS) is proposed to… More > Graphic Abstract

    Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-CatBoost

  • Open Access


    An Early Warning Model of Telecommunication Network Fraud Based on User Portrait

    Wen Deng1, Guangjun Liang1,2,3,*, Chenfei Yu1, Kefan Yao1, Chengrui Wang1, Xuan Zhang1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1561-1576, 2023, DOI:10.32604/cmc.2023.035016

    Abstract With the frequent occurrence of telecommunications and network fraud crimes in recent years, new frauds have emerged one after another which has caused huge losses to the people. However, due to the lack of an effective preventive mechanism, the police are often in a passive position. Using technologies such as web crawlers, feature engineering, deep learning, and artificial intelligence, this paper proposes a user portrait fraud warning scheme based on Weibo public data. First, we perform preliminary screening and cleaning based on the keyword “defrauded” to obtain valid fraudulent user Identity Documents (IDs). The basic… More >

  • Open Access


    Design of Cybersecurity Threat Warning Model Based on Ant Colony Algorithm

    Weiwei Lin1,2,*, Reiko Haga3

    Journal on Big Data, Vol.3, No.4, pp. 147-153, 2021, DOI:10.32604/jbd.2021.017299

    Abstract In this paper, a cybersecurity threat warning model based on ant colony algorithm is designed to strengthen the accuracy of the cybersecurity threat warning model in the warning process and optimize its algorithm structure. Through the ant colony algorithm structure, the local global optimal solution is obtained; and the cybersecurity threat warning index system is established. Next, the above two steps are integrated to build the cybersecurity threat warning model based on ant colony algorithm, and comparative experiment is also designed. The experimental results show that, compared with the traditional qualitative differential game-based cybersecurity More >

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