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Titlebook: Advances in Swarm Intelligence; First International Ying Tan,Yuhui Shi,Kay Chen Tan Conference proceedings 2010 The Editor(s) (if applicab

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樓主
發(fā)表于 2025-3-21 16:23:20 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances in Swarm Intelligence
期刊簡稱First International
影響因子2023Ying Tan,Yuhui Shi,Kay Chen Tan
視頻videohttp://file.papertrans.cn/150/149953/149953.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances in Swarm Intelligence; First International  Ying Tan,Yuhui Shi,Kay Chen Tan Conference proceedings 2010 The Editor(s) (if applicab
影響因子This book and its companion volume, LNCS vols. 6145 and 6146, constitute the proceedings of the International Conference on Swarm Intelligence (ICSI 2010) held in Beijing, the capital of China, during June 12-15, 2010. ICSI 2010 was the ?rst gathering in the world for researchers working on all aspects of swarm intelligence, and providedan academic forum for the participants to disseminate theirnewresearch?ndingsanddiscussemergingareasofresearch.Italsocreated a stimulating environment for the participants to interact and exchange inf- mation on future challenges and opportunities of swarm intelligence research. ICSI 2010 received 394 submissions from about 1241 authors in 22 countries and regions (Australia, Belgium, Brazil, Canada, China, Cyprus, Hong Kong, Hungary, India, Islamic Republic of Iran, Japan, Jordan, Republic of Korea, Malaysia, Mexico, Norway, Pakistan, South Africa, Chinese Taiwan, UK, USA, Vietnam) across six continents (Asia, Europe, North America, South America, Africa, and Oceania). Each submission was reviewed by at least three reviewers. Based on rigorous reviews by the Program Committee members and reviewers, 185 high-quality papers were selected for publicat
Pindex Conference proceedings 2010
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發(fā)表于 2025-3-21 22:43:03 | 只看該作者
0302-9743 viewed by at least three reviewers. Based on rigorous reviews by the Program Committee members and reviewers, 185 high-quality papers were selected for publicat978-3-642-13494-4978-3-642-13495-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
板凳
發(fā)表于 2025-3-22 03:56:41 | 只看該作者
地板
發(fā)表于 2025-3-22 05:48:34 | 只看該作者
Study on the Local Search Ability of Particle Swarm Optimizational optimum, even for unimodal functions. It is necessary to study the local search ability of PSO. The interval compression method and the probabilistic characteristic of the searching interval of particles are used to analyze the local search ability of PSO in this paper. The conclusion can be obta
5#
發(fā)表于 2025-3-22 09:52:33 | 只看該作者
The Performance Measurement of a Canonical Particle Swarm Optimizer with Diversive Curiosityive curiosity (CPSO/DC). A crucial idea here is to introduce diversive curiosity into the CPSO to comprehensively manage the trade-off between exploitation and exploration for alleviating stagnation. To demonstrate the effectiveness of the proposed method, computer experiments on a suite of five-dim
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發(fā)表于 2025-3-22 13:53:49 | 只看該作者
Mechanism and Convergence of Bee-Swarm Genetic Algorithmlobal search, and another for local search. Only best one can crossover. The genetic operators include order crossover operator, adaptive mutation operator and restrain operator. The simulated annealing is also introduced to help local optimization. The method sufficiently takes the advantage of gen
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發(fā)表于 2025-3-22 17:04:34 | 只看該作者
On the Farther Analysis of Performance of the Artificial Searching Swarm Algorithmous algorithms. For farther understanding the running principle of ASSA, this work discusses the functions of three behavior rules which decide the moves of searching swarm. Some typical functions are selected to do the simulation tests. The function simulation tests showed that the three behavior r
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發(fā)表于 2025-3-23 01:06:07 | 只看該作者
Orthogonality and Optimality in Non-Pheromone Mediated Foragingtructed which contains the location(s) of an item or of items in the search area. Collection is the task in which an item is picked up and carried back to a central known location. We theoretically examine these tasks, generating minimal conditions for each one to be accomplished. We then build a sw
9#
發(fā)表于 2025-3-23 03:29:27 | 只看該作者
An Adaptive Staged PSO Based on Particles’ Search Capabilitiesearch processes of the standard PSO (SPSO) and the linear decreasing inertia weight PSO (LDWPSO) are analyzed based on our previous definition of exploitation. Second, three stages of the search process in PSO are defined. Each stage has its own search preference, which is represented by the exploit
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發(fā)表于 2025-3-23 06:42:39 | 只看該作者
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