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Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries.

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第一作者： Hanan Abdullah,Mengash

第一单位： Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

作者： Hanan Abdullah,Mengash ^[1] ; Nuha,Alruwais ^[2] ; Fadoua,Kouki ^[3] ; Chinu,Singla ^[4] ; Elmouez Samir,Abd Elhameed ^[5] ; Ahmed,Mahmud ^[6]

作者单位： Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia. ^[1] Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, P.O. Box 22459, Riyadh 11495, Saudi Arabia. ^[2] Department of Financial and Banking Sciences, Applied College at Muhail Aseer, King Khalid University, Abha 61413, Saudi Arabia. ^[3] Department of Computer Science, University of the People, Pasadena, CA 91101, USA. ^[4] Department of Computer Science, College of Post-Graduated Studies, Sudan University of Science and Technology, Khartoum 11111, Sudan. ^[5] Research Center, Future University in Egypt, New Cairo 11835, Egypt. ^[6]

关键词 bio-inspired algorithms churn prediction feature selection metaheuristics telecom industry

DOI 10.3390/biomimetics9010001

PMID 38275449

发布时间 2024-10-23

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Biomimetics (Basel, Switzerland)

2023年9卷1期

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Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries.

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Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries.

Biomimetics (Basel, Switzerland)

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Biomimetics (Basel, Switzerland)

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