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检索条件"主题词=Quantum-Behaved Particle Swarm Optimization"
191 条 记 录,以下是1-10 订阅
排序:
quantum-behaved particle swarm optimization Based on Concentration Selection Probability Assignment Weights for Power System Economic Dispatch
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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2024年 第5期19卷 640-652页
作者: Wang, Miao Cao, Zhiao Li, Yuchun Northeastern Univ Sydney Smart Technol Coll 143 Taishan Rd Qinhuangdao 066004 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn 143 Taishan Rd Qinhuangdao 066004 Peoples R China Northeastern Univ Qinhuangdao Sch Comp & Commun Engn 143 Taishan Rd Qinhuangdao 066004 Peoples R China
The economic dispatch (ED) problem is very important in the economics of power systems, and a suitable dispatch algorithm can help power plants save huge amounts of money and use energy efficiently. To ensure the econ... 详细信息
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quantum-behaved particle swarm optimization with dynamic grouping searching strategy
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INTELLIGENT DATA ANALYSIS 2023年 第3期27卷 769-789页
作者: You, Qi Sun, Jun Palade, Vasile Pan, Feng Jiangnan Univ Sch Internet Things Engn Wuxi Jiangsu Peoples R China Jiangnan Univ Sch Artificial Intelligence & Comp Sci Wuxi Jiangsu Peoples R China Coventry Univ Ctr Computat Sci & Math Modeling Coventry W Midlands England
The quantum-behaved particle swarm optimization (QPSO) algorithm, a variant of particle swarm optimization (PSO), has been proven to be an effective tool to solve various of optimization problems. However, like other ... 详细信息
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Identifying influential spreaders in social networks: A two-stage quantum-behaved particle swarm optimization with Lévy flight
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Chinese Physics B 2024年 第1期33卷 743-754页
作者: 卢鹏丽 揽继茂 唐建新 张莉 宋仕辉 朱虹羽 Wenzhou Engineering Institute of Pump&Valve Lanzhou University of TechnologyWenzhou 325100China School of Computer and Communication Lanzhou University of TechnologyLanzhou 730050China
The influence maximization problem aims to select a small set of influential nodes, termed a seed set, to maximize their influence coverage in social networks. Although the methods that are based on a greedy strategy ... 详细信息
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quantum-behaved particle swarm optimization-based active noise control system with timing varying path
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JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL 2021年 第1期40卷 524-539页
作者: Yu, Ning Li, Zhaoxia Wu, Yinfeng Feng, Renjian Beihang Univ Sch Instrumentat & Optoelect Engn Beijing Peoples R China
Active noise control systems can effectively suppress the impact of low-frequency noise and they have been applied in many fields. Recently, the evolutionary computation algorithm-based active noise control system has... 详细信息
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Multi-region hierarchical surrogate-assisted quantum-behaved particle swarm optimization for expensive optimization problems
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EXPERT SYSTEMS WITH APPLICATIONS 2025年 261卷
作者: Li, Chao Zhang, Quanshu Palade, Vasile Lu, Hengyang Sun, Jun Jiangnan Univ Sch Artificial Intelligence & Comp Sci 1800 Lihu Ave Wuxi 214122 Jiangsu Peoples R China Coventry Univ Ctr Computat Sci & Math Modelling Coventry CV1 2TL England
Surrogate-assisted evolutionary algorithms (SAEAs) have been successfully applied to solve computationally expensive optimization problems. However, most SAEAs struggle to achieve good results in solving complex multi... 详细信息
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Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization
ROBOTIC INTELLIGENCE AND AUTOMATION
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ROBOTIC INTELLIGENCE AND AUTOMATION 2023年 第3期43卷 267-289页
作者: Zhou, Binghai Huang, Yufan Tongji Univ Sch Mech Engn Shanghai Peoples R China
PurposeThe purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application o... 详细信息
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quantum-behaved particle swarm optimization Fault-Tolerant Control for Human Occupied Vehicle  14th
Quantum-Behaved Particle Swarm Optimization Fault-Tolerant C...
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14th International Conference on Intelligent Robotics and Applications (ICIRA)
作者: Zhang, Huapeng Zhu, Daqi Shanghai Maritime Univ Shanghai Engn Res Ctr Intelligent Maritime Search Haigang Ave 1550 Shanghai 201306 Peoples R China
In this paper, for the human occupied vehicle (HOV) system, the control strategies are used to reallocate the thruster forces based on quantum-behaved particle swarm optimization (QPSO). QPSO is adopted in terms of th... 详细信息
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An adaptive binary quantum-behaved particle swarm optimization algorithm for the multidimensional knapsack problem
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swarm AND EVOLUTIONARY COMPUTATION 2024年 86卷
作者: Li, Xiaotong Fang, Wei Zhu, Shuwei Zhang, Xin Jiangnan Univ Jiangsu Prov Engn Lab Pattern Recognit & Comp Inte Wuxi Peoples R China
The multidimensional knapsack problem (MKP) is a classical combinatorial optimization problem with wide real -life applications. Binary quantum -behaved particle swarm optimization (BQPSO) algorithm is a popular heuri... 详细信息
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quantum-behaved particle swarm optimization Algorithm Based on the Two-Body Problem
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Chinese Journal of Electronics 2019年 第3期28卷 569-576页
作者: YAN Tao LIU Fengxian Institute of Big Data Science and Industry Shanxi University School of Computer and Information Technology Shanxi University Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Guangzhou Institute of Electronic Technology Chinese Academy of Sciences University of Chinese Academy of Sciences
The present study proposes an improved quantum-behaved particle swarm optimization algorithm based on the two-body problem model(QTPSO) for solving the problem that other quantum-behaved particle swarm optimization al... 详细信息
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An improved binary quantum-behaved particle swarm optimization algorithm for knapsack problems
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INFORMATION SCIENCES 2023年 第1期648卷
作者: Li, Xiaotong Fang, Wei Zhu, Shuwei Jiangnan Univ Jiangsu Prov Engn Lab Pattern Recognit & Computat Wuxi Peoples R China
The 0-1 knapsack problem is a typical NP-hard combinatorial optimization problem that is difficult to solve efficiently based on traditional optimization approaches. Binary quantum behaved particle swarm optimization ... 详细信息
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