机构

• 长春光学精密机械与物... [1]
• 自动化研究所 [1]
• 生态环境研究中心 [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2021 [1]
• 2020 [1]
• 2007 [1]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems 期刊论文  OAI收割 SUSTAINABILITY, 2021, 卷号: 13, 期号: 19, 页码: 27 作者:  Lodhi, Ehtisham;  Wang, Fei-Yue;  Xiong, Gang;  Mallah, Ghulam Ali;  Javed, Muhammad Yaqoob   |  收藏  |  浏览/下载：29/0  |  提交时间：2022/01/27 photovoltaic (PV)  partial shading  maximum power point tracking (MPPT)  dragonfly optimization algorithm (DOA)  adaptive cuckoo search optimization (ACSO)  fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN)  improved particle swarm optimization (IPSO)  voltage source inverter (VSI)  total harmonic distortion (THD)   Monthly Streamflow Forecasting Using ELM-IPSO Based on Phase Space Reconstruction 期刊论文  OAI收割 WATER RESOURCES MANAGEMENT, 2020, 卷号: 34, 期号: 11, 页码: 3515-3531 作者:  Jiang, Yan;  Bao, Xin;  Hao, Shaonan;  Zhao, Hongtao;  Li, Xuyong   |  收藏  |  浏览/下载：22/0  |  提交时间：2021/08/31 Streamflow prediction  Chaohe River basin  Chaotic dynamic characteristics  Phase space reconstruction  Extreme learning machine  Improved particle swarm optimization algorithm   An improved discrete particle swarm optimization algorithm for TSP (EI CONFERENCE) 会议论文  OAI收割 2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007, November 2, 2007 - November 5, 2007, Silicon Valley, CA, United states 作者:  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y. 收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25 An Improved discrete particle swarm optimization (DPSO)-based algorithm for the traveling salesman problem (TSP) is proposed. In order to overcome the problem of premature convergence  a novel depressor is proposed and a diversity measure to control the swarm is also introduced which can be used to switch between the attractor and depressor. The proposed algorithm has been applied to a set of benchmark problems and compared with the existing algorithms for solving TSP using swarm intelligence. The results show that it can prevent premature convergence to a high degree  but still keeps a rapid convergence like the basic DPSO. 2007 IEEE.