Improved whale optimization algorithm based on the tent chaotic mapping and nonlinear convergence factor
文献类型：会议论文
| 作者 | Dong SX(董淑娴)1,2,3; Bu CG(卜春光)1,3 ; Wang YL(王勇亮)1,2,3
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| 出版日期 | 2020 |
| 会议日期 | September 11-13, 2020 |
| 会议地点 | Shangri-La, China |
| 页码 | 1-8 |
| 英文摘要 | To overcome the shortcomings of whale optimization algorithm (WOA) such as the slow convergence rate, and low convergence accuracy, and being easy to fall into the local optimum, an improved whale optimization algorithm based on the tent chaotic mapping and nonlinear convergence factor (TNWOA)is proposed. Firstly, In this algorithm, tent chaotic mapping, which enhances the diversity of the initialization population, is introduced into the initialization of population, therefore, the search space can be searched more thoroughly; Secondly, trigonometric function and the beta distribution are introduced in the convergence factor 'a', which balance the global search ability as well as local optimization ability and speed up the convergence speed of the algorithm. Simulation experiments on the four kinds of common test functions on CEC2017 show that under the same experimental conditions, the improved whale optimization algorithm improves the solution accuracy and convergence speed significantly, and its performance is obviously better than other smart optimization algorithms and other improved WOA algorithms. |
| 产权排序 | 1 |
| 会议录 | 2020 International Conference on Machine Learning and Computer Application
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| 会议录出版者 | IOP |
| 会议录出版地 | Bristol, UK |
| 语种 | 英语 |
| ISSN号 | 1742-6588 |
| 源URL | [http://ir.sia.cn/handle/173321/27969]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Bu CG(卜春光) |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
| 推荐引用方式 GB/T 7714 | Dong SX,Bu CG,Wang YL. Improved whale optimization algorithm based on the tent chaotic mapping and nonlinear convergence factor[C]. 见:. Shangri-La, China. September 11-13, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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