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A new workload prediction model using extreme learning machine and enhanced tug of war optimization
Názov A new workload prediction model using extreme learning machine and enhanced tug of war optimization Autor Nguyen Thieu Spoluautori Hoang Bao Nguyen Giang 1972- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Nguyen Binh Minh SCOPUS RID ORCID Zdroj.dok. Procedia Computer Science. Vol. 170 (2020), p. 362-369 Jazyk dok. eng - angličtina Druh dok. rozpis článkov z periodík (rbx) Ohlasy ZHANG, Hong - HOANG NGUYEN - DIEP-ANH VU - XUAN-NAM BUI - PRADHAN, Biswajeet. Forecasting monthly copper price: A comparative study of various machine learning-based methods. In RESOURCES POLICY. ISSN 0301-4207, 2021, vol. 73, no., pp. XUAN-NAM BUI - HOANG NGUYEN - QUANG-HIEU TRAN - DINH-AN NGUYEN - HOANG-BAC BUI. Predicting Blast-induced Ground Vibration in Quarries Using Adaptive Fuzzy Inference Neural Network and Moth-Flame Optimization. In NATURAL RESOURCES RESEARCH. ISSN 1520-7439, 2021, vol. 30, no. 6, pp. 4719-4734. Dostupné na: https://doi.org/10.1007/s11053-021-09968-5. LI, Ning - HOANG NGUYEN - ROSTAMI, Jamal - ZHANG, Wengang - BUI, Xuan-Nam - PRADHAN, Biswajeet. Predicting rock displacement in underground mines using improved machine learning-based models. In MEASUREMENT. ISSN 0263-2241, 2022, vol. 188, no., pp. Dostupné na: https://doi.org/10.1016/j.measurement.2021.110552. RAI, Rebika - DAS, Arunita - RAY, Swarnajit - DHAL, Krishna Gopal. Human-Inspired Optimization Algorithms: Theoretical Foundations, Algorithms, Open-Research Issues and Application for Multi-Level Thresholding. In ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2022, vol., no., pp. ISSN 1134-3060. Dostupné na: https://doi.org/10.1007/s11831-022-09766-z. SHI, Jinmei - LEAU, Yu-Beng - LI, Kun. SAVE-AS: Accelerating convergence in network traffic prediction through adaptive optimized variational mode decomposition and an integrated extreme learning machine. In INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2022, vol. 35, no. 10, pp. ISSN 1074-5351. Dostupné na: https://doi.org/10.1002/dac.5164. LIANG, Rui - LE-HUNG, Tien - NGUYEN-THOI, Trung. Energy consumption prediction of air-conditioning systems in eco-buildings using hunger games search optimization-based artificial neural network model. In JOURNAL OF BUILDING ENGINEERING, 2022, vol. 59, no., pp. Dostupné na: https://doi.org/10.1016/j.jobe.2022.105087. BUI, Xuan Nam - NGUYEN, Hoang - SOUKHANOUVONG, Phonepaserth. Extra Trees Ensemble: A Machine Learning Model for Predicting Blast-Induced Ground Vibration Based on the Bagging and Sibling of Random Forest Algorithm. In Lecture Notes in Civil Engineering, 2022-01-01, 228, pp. 643-652. ISSN 23662557. Dostupné na: https://doi.org/10.1007/978-981-16-9770-8_43. NGUYEN, Hoang - TINH, Nguyen Tam - TIEN, Dinh. Utilizing a Bagging Model Based on Decision Trees and k-nearest Neighbors for Predicting Slope Stability in Open Pit Mines. In Lecture Notes in Civil Engineering, 2022-01-01, 228, pp. 633-642. ISSN 23662557. Dostupné na: https://doi.org/10.1007/978-981-16-9770-8_42. YADAV, Archana - KUSHWAHA, Shivam - GUPTA, Jyoti - SAXENA, Deepika - SINGH, Ashutosh Kumar. A Survey of the Workload Forecasting Methods in Cloud Computing. In Lecture Notes in Electrical Engineering, 2022-01-01, 915, pp. 539-547. ISSN 18761100. Dostupné na: https://doi.org/10.1007/978-981-19-2828-4_49. RASTGOO, A. - KHAJAVI, H. A novel study on forecasting the airfoil self-noise, using a hybrid model based on the combination of CatBoost and Arithmetic Optimization Algorithm. In EXPERT SYSTEMS WITH APPLICATIONS. ISSN 0957-4174, NOV 1 2023, vol. 229, A. Dostupné na: https://doi.org/10.1016/j.eswa.2023.120576. YEKTA, Mohammad - SHAHHOSEINI, Hadi Shahriar. A Review on Machine Learning Methods for Workload Prediction in Cloud Computing. In 2023 13th International Conference on Computer and Knowledge Engineering, ICCKE 2023, 2023-01-01, pp. 306-311. Dostupné na: https://doi.org/10.1109/ICCKE60553.2023.10326297. JOSHAGHANI, M. - BARAK, S. - ASADI, A. - MIRAFZALI, E. Retail time series forecasting using an automated deep meta-learning framework. In Available at SSRN. 2023, pp. 1-33. doi: 10.2139/ssrn.4393300. ZHONG, Rui - ZHANG, Chao - YU, Jun. Chaotic vegetation evolution: leveraging multiple seeding strategies and a mutation module for global optimization problems. In EVOLUTIONARY INTELLIGENCE, 2024, vol. 17, no. 4, pp. 2387-2411. ISSN 1864-5909. Dostupné na: https://doi.org/10.1007/s12065-023-00892-6. SALEH, Azlan - ZULKIFLEY, Mohd Asyraf. Prediction of suspended sediment load in Sungai Semenyih using extreme learning machines and metaheuristic optimization approach. In JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2025, vol. 380, no., art. no. 124987. ISSN 0301-4797. Dostupné na: https://doi.org/10.1016/j.jenvman.2025.124987. CHANDNANI, Chirag Jitendra - AGARWAL, Vedik - KULKARNI, Shlok Chetan - AREN, Aditya - AMALI, D. Geraldine Bessie - SRINIVASAN, Kathiravan. A Physics-Based Hyper Parameter Optimized Federated Multi-Layered Deep Learning Model for Intrusion Detection in IoT Networks. In IEEE ACCESS, 2025, vol. 13, no., pp. 21992-22010. ISSN 2169-3536. Dostupné na: https://doi.org/10.1109/ACCESS.2025.3535952. ZHANG, Weijian - KONG, Min - ZHANG, Yajing - FATHOLLAHI-FARD, Amir M. - TIAN, Guangdong. A revised deep reinforcement learning algorithm for parallel machine scheduling problem under multi-scenario due date constraints. In SWARM AND EVOLUTIONARY COMPUTATION, 2025, vol. 92, no., art. no. 101808. ISSN 2210-6502. Dostupné na: https://doi.org/10.1016/j.swevo.2024.101808. DUBEY, Saurabh - GUPTA, Deepak - MALLIK, Mainak. Extreme learning machine to foretell the deflection in plain cement, steel-reinforced, and bamboo-reinforced concrete beams. In Emerging Materials Research, 2025-03-14, 14, 1, pp. 12-27. ISSN 20460147. Dostupné na: https://doi.org/10.1680/jemmr.24.00046. Kategória ADMB - Vedecké práce v zahraničných neimpaktovaných časopisoch registrovaných vo WOS Core Collection alebo SCOPUS Kategória (od 2022) V3 - Vedecký výstup publikačnej činnosti z časopisu Typ výstupu článok Rok vykazovania 2020 Registrované v WOS Registrované v SCOPUS DOI 10.1016/j.procs.2020.03.063 
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