机构

• 遥感与数字地球研究所 [2]
• 长春光学精密机械与物... [1]
• 自动化研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 会议论文 [3]
• 学位论文 [1]

发表日期

• 2013 [1]
• 2010 [2]
• 2007 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4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 群体智能优化算法及其在控制器参数整定中的应用 学位论文  OAI收割 工程硕士, 中国科学院自动化研究所: 中国科学院大学, 2013 作者:  韩久琦 收藏  |  浏览/下载：215/0  |  提交时间：2015/09/02 群体智能优化算法  果蝇优化算法  粒子群算法  PID控制器  Swarm intelligence optimization algorithms  fruit fly optimization algorithm  particle swarm optimization  PID controllers   A hybrid PSO/ACO algorithm for land cover classification 会议论文  OAI收割 2nd International Conference on Information Science and Engineering, ICISE2010,, Hangzhou, China, December 4, 2010 - December 6,2010 Dai, Qin 收藏  |  浏览/下载：20/0  |  提交时间：2014/12/07 Particle swarm optimization (PSO)  Algorithms  Artificial intelligence  Cellular automata  Image analysis  Image classification  Image reconstruction  Information science  Landforms  Remote sensing   Remote sensing image change detection based on swarm intelligent algorithm 会议论文  OAI收割 2010 International Conference on Multimedia Technology, ICMT 2010,, Ningbo, China, October 29, 2010 - October 31,2010 Dai, Qin; Liu, Jianbo; Liu, Shibin 收藏  |  浏览/下载：22/0  |  提交时间：2014/12/07 Algorithms  Artificial intelligence  Cellular automata  Data handling  Image reconstruction  Particle swarm optimization (PSO)  Remote sensing  Signal detection   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：28/0  |  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.