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检索条件"主题词=offline data-driven optimization"
7 条 记 录,以下是1-10 订阅
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Multifidelity surrogates-assisted multi-objective particle swarm algorithm for offline data-driven optimization
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APPLIED INTELLIGENCE 2024年 第22期54卷 11649-11671页
作者: Cui, Yingying Meng, Xi Qiao, Junfei Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Lab Smart Environm Protect Beijing 100124 Peoples R China Minist Educ Engn Res Ctr Intelligent Percept & Autonomous Cont Beijing 100124 Peoples R China
Surrogate-assisted evolutionary algorithms have been widely employed to solve data-driven optimization problems. However, for offline data-driven optimization, it is very challenging to perform evolutionary search eff... 详细信息
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offline data-driven Evolutionary optimization Using Selective Surrogate Ensembles
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2019年 第2期23卷 203-216页
作者: Wang, Handing Jin, Yaochu Sun, Chaoli Doherty, John Univ Surrey Dept Comp Sci Guildford GU2 7XH Surrey England Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Liaoning Peoples R China Taiyuan Univ Sci & Technol Dept Comp Sci & Technol Taiyuan 030024 Shanxi Peoples R China Univ Surrey Dept Mech Engn Sci Guildford GU2 7XH Surrey England
In solving many real-world optimization problems, neither mathematical functions nor numerical simulations are available for evaluating the quality of candidate solutions. Instead, surrogate models must be built based... 详细信息
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offline data-driven Multiobjective optimization: Knowledge Transfer Between Surrogates and Generation of Final Solutions
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2020年 第3期24卷 409-423页
作者: Yang, Cuie Ding, Jinliang Jin, Yaochu Chai, Tianyou Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Univ Surrey Dept Comp Sci Guildford GU2 7XH Surrey England
In offline data-driven optimization, only historical data is available for optimization, making it impossible to validate the obtained solutions during the optimization. To address these difficulties, this paper propo... 详细信息
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offline data-driven Evolutionary optimization Algorithm Using K-Fold Cross  13th
Offline Data-Driven Evolutionary Optimization Algorithm Usin...
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13th International Conference on Swarm Intelligence (ICSI)
作者: Wang, Mengzhen Shan, Yawen Xu, Fei Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China
In the field of science and engineering, there are many offline data-driven optimization problems, which have no mathematical functions, and cannot use numerical simulations or physical experiments, but can only use t... 详细信息
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offline data-driven Particle Swarm optimization Assisted by Selective Surrogate Ensembles and Hybrid Search Strategies  34
Offline Data-Driven Particle Swarm Optimization Assisted by ...
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34th Chinese Control and Decision Conference (CCDC)
作者: Wei, Jiamin Niu, Haoyu Xidian Univ Sch Telecommun Engn State Key Lab ISN Xian 710071 Peoples R China Univ Calif Merced Sch Engn Merced CA 95343 USA
Real-world optimization problems usually involve the case of offline data-driven optimization, where any real fitness evaluations are not allowed during the optimization. Although surrogate models can be used for fitn... 详细信息
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offline data-driven Particle Swarm optimization Assisted by Selective Surrogate Ensembles and Hybrid Search Strategies
Offline Data-Driven Particle Swarm Optimization Assisted by ...
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第34届中国控制与决策会议
作者: Jiamin Wei Haoyu Niu State Key Laboratory of ISN School of Telecommunications EngineeringXidian University School of Engineering University of California
Real-world optimization problems usually involve the case of offline data-driven optimization,where any real fitness evaluations are not allowed during the *** surrogate models can be used for fitness approximation,it... 详细信息
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A Gaussian Process Assisted offline Estimation of Multivariate Gaussian Distribution Algorithm
A Gaussian Process Assisted Offline Estimation of Multivaria...
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IEEE International Conference on Systems, Man, and Cybernetics (SMC)
作者: Ma, Xin-Xin Chen, Wei-Neng Yang, Qiang South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China Nanjing Univ Informat Sci & Technol Sch Artificial Intelligence Nanjing Jiangsu Peoples R China
Surrogated assisted evolutionary algorithms are commonly used to solve real-world expensive optimization problems. However, in some situations, no online data is available during the evolution process. In this situati... 详细信息
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