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Van-Tinh Nguyen, Vu-Minh Tran and Ngoc-Tam Bui
Differential evolution (DE) is one of the best evolutionary algorithms (EAs). In recent decades, many techniques have been developed to enhance the performance of this algorithm, such as the Improve Self-Adaptive Differential Evolution (ISADE) algorithm....
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Xiaoling Wang, Qi Kang, Mengchu Zhou, Zheng Fan and Aiiad Albeshri
Multi-task optimization (MTO) is a novel emerging evolutionary computation paradigm. It focuses on solving multiple optimization tasks concurrently while improving optimization performance by utilizing similarities among tasks and historical optimization...
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Jiajia Fan, Wentao Huang, Qingchao Jiang and Qinqin Fan
For multimodal multi-objective optimization problems (MMOPs), there are multiple equivalent Pareto optimal solutions in the decision space that are corresponding to the same objective value. Therefore, the main tasks of multimodal multi-objective optimiz...
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Yu Jiang, Changyu Qian, Jie Yu, Luyao Zhou, Zheng Wang, Qian Chen, Yang Wang and Xiaole Ma
As the double carbon target continues to be promoted and the installed capacity of gas-fired power generation gradually expands, whether and when gas-fired power generation should enter the market is a major concern for the industry. This paper analyzes ...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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