A novel neural network training algorithm based on particle swarm optimizer and optimal foraging theory
文献类型：期刊论文
| 作者 | Niu B(牛奔); Zhu YL(朱云龙) ; Hu KY(胡琨元); He XX(何小贤)
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| 刊名 | DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS
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| 出版日期 | 2007 |
| 卷号 | 14期号:S页码:370-375 |
| 关键词 | particle swarm optimization optimal foraging theory neural network |
| ISSN号 | 1492-8760 |
| 产权排序 | 1 |
| 通讯作者 | 牛奔 |
| 中文摘要 | A novel neural network training algorithm based on particle swarm optimization (PSO) and optimal foraging theory (OFT) is presented in this paper. The proposed algorithm, called PSOOFT, makes use of two mechanisms of OFT: a reproduction strategy to enhance the ability to converge rapidly to good solutions and a patch-choice based scheme to keep a right balance of exploration, and exploitation, The PSOOFT is applied for training a multi-layer feed-forward neural network for three benchmark classification problems. The performance of PSOOFT used for neural network training is compared to that of Back Propagation (BP), genetic algorithm (GA) and standard PSO (SPSO), demonstrating its effectiveness and efficiency. |
| 收录类别 | CPCI（ISTP） |
| 语种 | 英语 |
| WOS记录号 | WOS:000252392000061 |
| 公开日期 | 2012-05-29 |
| 源URL | [http://ir.sia.cn/handle/173321/6871]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室_先进制造技术研究室 |
| 推荐引用方式 GB/T 7714 | Niu B,Zhu YL,Hu KY,et al. A novel neural network training algorithm based on particle swarm optimizer and optimal foraging theory[J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS,2007,14(S):370-375. |
| APA | Niu B,Zhu YL,Hu KY,&He XX.(2007).A novel neural network training algorithm based on particle swarm optimizer and optimal foraging theory.DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS,14(S),370-375. |
| MLA | Niu B,et al."A novel neural network training algorithm based on particle swarm optimizer and optimal foraging theory".DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS 14.S(2007):370-375. |
入库方式： OAI收割
来源：沈阳自动化研究所
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