| 一种自适应粒子群算法的小波神经网络优化 |
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| 引用本文： | 刘志勇,王小红.一种自适应粒子群算法的小波神经网络优化[J].机械与电子,2021,39(8):8-12. |
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| 作者姓名： | 刘志勇 王小红 |
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| 作者单位： | １． 咸阳职业技术学院,陕西 咸阳 ７１２０００ ;?２． 陕西省委党校,陕西 西安 ７１００６１? |
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| 摘 要： | 针对传统粒子群算法易陷入局部最优解的问题,提出了一种变权重粒子群算法.该算法通过引入交叉权重因子和粒子个体状态最优权值,对传统粒子群算法进行了优化,使粒子在移动过程中利用更多的信息来调整各自的移动方向,扩大粒子在运动过程中的自我认知范围,提高了粒子群算法的收敛精度和收敛速度.最后,利用改进的变权重粒子群算法对小波神经网络控制器进行优化,有效地验证了变权重粒子群算法的精确性.
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| 关 键 词： | 变权重 粒子群算法 全局最优 小波神经网络 |
A Wavelet Neural Network Optimization Method Based on Variable-Weight Particle Swarm Optimization |
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| LIU Zhiyong,WANG Xiaohong.A Wavelet Neural Network Optimization Method Based on Variable-Weight Particle Swarm Optimization[J].Machinery & Electronics,2021,39(8):8-12. |
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| Authors: | LIU Zhiyong WANG Xiaohong |
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| Affiliation: | (１．Xianyang Vocational and Technical College , Xianyang ７１２０００ , China ;２． Shaanxi Provincial Party School of the CPC , Xi ’ an ７１００６１ , China ) |
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| Abstract: | A variable-weight particle swarm optimization ( VWPSO ) algorithm is proposed to overcome the shortcoming of the traditional particle swarm optimization ( PSO ) algorithm , which is easy to fall into the local optimal solution． In the proposed strategy , the weight factor and the optimal weight of individual state are in troduced to adjust the moving direction of the particles via the more information , and the self-awareness range of particles in the process of motion is expanded．Moreover , the convergence accuracy and convergence speed of particle swarm optimization algorithm are improved．Finally , the VWPSO algorithm is used to optimize the wavelet neural network controller , which verifies the accuracy of the VWPSO algorithm effectively． |
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| Keywords: | variable-weight particle swarm optimization global optimum wavelet neural network |
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