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Analysis and Improvement of Extremum Random Disturbed Arithmetic Operator of a PSO Algorithm

机译:PSO算法极值随机扰动算术运算算机的分析与改进

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Aiming at the demerits of extremum random disturbed arithmetic operator of a particle swarm optimization algorithm, the reasonable amelioration is put forward based on the design idea of extremum random disturbed arithmetic operator. An improved particle swarm optimization algorithm is put forward and applied to parameter selection of support vector machine. The regress modeling of two common functions based on least square support vector machine is to be as examples and the simulation experiment is done. The results show that the amelioration of arithmetic operator is necessary and feasible. The convergence velocity and precision of algorithm are enhanced.
机译:针对粒子群优化算法的极值随机扰动算术算子的缺点,基于极值随机扰动算术运算符的设计思想,提出了合理的改进。提出了一种改进的粒子群优化算法,并应用于支持向量机的参数选择。基于最小二乘支持向量机的两个常见功能的回归建模是作为示例,并完成模拟实验。结果表明,算术运营商的改善是必要的,可行的。增强了算法的收敛速度和精度。

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