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检索条件"主题词=Moth-flame optimization algorithm"
59 条 记 录,以下是11-20 订阅
A Novel Gated Recurrent Unit Network Based on SVM and moth-flame optimization algorithm for Behavior Decision-Making of Autonomous Vehicles
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IEEE ACCESS 2021年 9卷 20410-20422页
作者: Yin, Taiqiao Li, Ying Fan, Jiahao Wang, Tan Shi, Yunxia Jilin Univ Coll Software Changchun 130012 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ Changchun 130012 Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Space Technol Jilin Co Ltd Jilin 132013 Jilin Peoples R China
The behavior decision-making algorithm plays an important role in ensuring the safe driving of autonomous vehicles. However, existing behavior decision-making methods lack the capability to cope with future motion unc... 详细信息
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The moth-flame optimization algorithm of Abrasive Water Jet Cutting Process
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Procedia Computer Science 2024年 246卷 2912-2921页
作者: Elżbieta Kawecka Piotr Puzio The Jacob of Paradies University Faculty of Technology Teatralna 25 66-400 Gorzów Wielkopolski Poland
The article presents the possibility of using the moth-flame optimization (MFO) algorithm for Abrasive Water Jet machining (AWJ) of structural steel materials. In order to carry out the optimization, an original progr... 详细信息
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An improved moth-flame optimization algorithm with periodic mutation and Gaussian mutation for safety-enhanced UAV path planning
An improved moth-flame optimization algorithm with periodic ...
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第43届中国控制会议
作者: Xiaodong Zhao Zhiqiang Hu Xiaoqian Li Xianliang Zhang School of Mathematics and Statistics Taishan University
To handle the path planning problem of unmanned aerial vehicles(UAV) meeting numerous obstacles in complicated environments, an improved moth-flame optimization(MFO) algorithm with periodic and Gaussian mutations(PGMF... 详细信息
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An improved moth-flame optimization algorithm based on fusion mechanism  47
An improved moth-flame optimization algorithm based on fusio...
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47th Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)
作者: Jiang, Luchao Hao, Kuangrong Tang, Xue-song Wang, Tong Liu, Xiaoyan Donghua Univ Coll Informat Sci & Technol Shanghai Peoples R China
moth-flame optimization algorithms are widely employed to solve optimization problems and achieve good performance. However, the algorithms suffer the shortcoming of prematurity because of the early gathering of flame... 详细信息
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A covariance-based moth-flame optimization algorithm with Cauchy mutation for solving numerical optimization problems
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APPLIED SOFT COMPUTING 2022年 第0期119卷 108538-108538页
作者: Zhao, Xiaodong Fang, Yiming Liu, Le Xu, Miao Li, Qiang Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Peoples R China Yanshan Univ Engn Res Ctr Minist Educ Intelligent Control Syst & Intelligent Qinhuangdao 066004 Peoples R China Hebei Normal Univ Coll Engn Shijiazhuang 050024 Peoples R China
moth-flame optimization (MFO) algorithm, which is inspired by the navigation method of moths, is a nature-inspired optimization algorithm. The MFO is easy to implement and has been used to solve many real-world optimi... 详细信息
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Multi-swarm improved moth-flame optimization algorithm with chaotic grouping and Gaussian mutation for solving engineering optimization problems
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EXPERT SYSTEMS WITH APPLICATIONS 2022年 204卷
作者: Zhao, Xiaodong Fang, Yiming Ma, Shuidong Liu, Zhendong Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Hebei Peoples R China Yanshan Univ Engn Res Ctr Minist Educ Intelligent Control Syst & Intelligen Qinhuangdao 066004 Hebei Peoples R China North China Univ Sci & Technol Coll Continuing Educ Tangshan 063210 Peoples R China
moth-flame optimization (MFO) is widely utilized to solve optimization problems in different fields since it has a simple structure and easy implementation. However, MFO cannot effectively balance exploration and expl... 详细信息
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An improved moth-flame optimization algorithm with orthogonal opposition-based learning and modified position updating mechanism of moths for global optimization problems
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APPLIED INTELLIGENCE 2020年 第12期50卷 4434-4458页
作者: Zhao, Xiaodong Fang, Yiming Liu, Le Li, Jianxiong Xu, Miao Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Hebei Peoples R China Yanshan Univ Minist Educ Intelligent Control Syst & Intelligen Res Ctr Qinhuangdao 066004 Hebei Peoples R China
moth-flame optimization (MFO) algorithm is a new population-based meta-heuristic algorithm for solving global optimization problems. flames generation and spiral search are two key components that affect the performan... 详细信息
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Optimal design of automobile structures using moth-flame optimization algorithm and response surface methodology
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MATERIALS TESTING 2020年 第4期62卷 371-377页
作者: Yildiz, Betul Sultan YOK UAK Bursa Turkey Bursa Uludag Univ Bursa Bursa Turkey Bursa Tech Univ Mech Engn Bursa Turkey
In order to present an integrated approach to optimal automobile component design, this research is focused on a shape optimization problem of a bracket using moth-flame optimization algorithm (MFO) and response surfa... 详细信息
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An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation
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JOURNAL OF CLEANER PRODUCTION 2020年 253卷 119966-119966页
作者: Lin, Guo-Qian Li, Ling-Ling Tseng, Ming-Lang Liu, Han-Min Yuan, Dong-Dong Tan, Raymond R. Hebei Univ Technol State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300130 Peoples R China Hebei Univ Technol Key Lab Electromagnet Field & Elect Apparat Relia Tianjin 300130 Peoples R China Asia Univ Inst Innovat & Circular Econ Taichung Taiwan China Med Univ China Med Univ Hosp Dept Med Res Taichung Taiwan Univ Kebangsaan Malaysia Fac Econ & Management Bangi Malaysia ZhangJiakou Wind Photovolta & Energy Storage Demo Zhangjiakou 075061 Peoples R China De La Salle Univ Gokongwei Coll Engn Chem Engn Dept Manila Philippines
With the expansion of grid-connected solar power generation, the variability of photovoltaic power generation has become increasingly pronounced. Accurate photovoltaic output prediction is necessary to ensure power sy... 详细信息
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DMFO-CD: A Discrete moth-flame optimization algorithm for Community Detection
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algorithmS 2021年 第11期14卷 314页
作者: Nadimi-Shahraki, Mohammad H. Moeini, Ebrahim Taghian, Shokooh Mirjalili, Seyedali Islamic Azad Univ Najafabad Branch Fac Comp Engn Najafabad *** Iran Islamic Azad Univ Najafabad Branch Big Data Res Ctr Najafabad *** Iran Torrens Univ Australia Ctr Artificial Intelligence Res & Optimisat Fortitude Valley Qld 4006 Australia Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea
In this paper, a discrete moth-flame optimization algorithm for community detection (DMFO-CD) is proposed. The representation of solution vectors, initialization, and movement strategy of the continuous moth-flame opt... 详细信息
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