Information entropy and interaction optimization model based on swarm intelligence
文献类型:期刊论文
作者 | He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben |
刊名 | Advances in natural computation, pt 2
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出版日期 | 2006 |
卷号 | 4222页码:136-145 |
ISSN号 | 0302-9743 |
通讯作者 | He, xiaoxian(hexiaoxian@sia.cn) |
英文摘要 | By introducing the information entropy h(x) and mutual information i(x; y) of information theory into swarm intelligence, the interaction optimization model (iom) is proposed. in this model, the information interaction process of individuals is analyzed with h(x) and i(x; y) aiming at solving optimization problems. we call this optimization approach as interaction optimization. in order to validate this model, we proposed a new algorithm for traveling salesman problem (tsp), namely route-exchange algorithm (rea), which is inspired by the information interaction of individuals in swarm intelligence. some benchmarks are tested in the experiments. the results indicate that the algorithm can quickly converge to the optimal solution with quite low cost. |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods |
语种 | 英语 |
WOS记录号 | WOS:000241892100018 |
出版者 | SPRINGER-VERLAG BERLIN |
URI标识 | http://www.irgrid.ac.cn/handle/1471x/2379538 |
专题 | 中国科学院大学 |
通讯作者 | He, Xiaoxian |
作者单位 | 1.Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | He, Xiaoxian,Zhu, Yunlong,Hu, Kunyuan,et al. Information entropy and interaction optimization model based on swarm intelligence[J]. Advances in natural computation, pt 2,2006,4222:136-145. |
APA | He, Xiaoxian,Zhu, Yunlong,Hu, Kunyuan,&Niu, Ben.(2006).Information entropy and interaction optimization model based on swarm intelligence.Advances in natural computation, pt 2,4222,136-145. |
MLA | He, Xiaoxian,et al."Information entropy and interaction optimization model based on swarm intelligence".Advances in natural computation, pt 2 4222(2006):136-145. |
入库方式: iSwitch采集
来源:中国科学院大学
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