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于 2019-01-13 发布
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说明:  针对差分进化( DE) 算法后期收敛速度变慢、收敛精度变低以及易陷入局部最优解的缺点,提出一种基于双种群自适应进化的改进差分进化算法。(To overcome the shortcomings of slow convergence speed, low convergence accuracy and easy to fall into local optimal solution of differential evolution (DE) algorithm, a new algorithm is proposed. An improved differential evolution algorithm for adaptive evolution of two populations.)

文件列表:

基于改进差分进化算法优化极限学习机的短期负荷预测\基于差分进化算法的微电网多目标优化调度(三个目标).caj, 372767 , 2019-01-10
基于改进差分进化算法优化极限学习机的短期负荷预测\基于改进差分进化算法优化极限学习机的短期负荷预测.caj, 500314 , 2019-01-10
基于改进差分进化算法优化极限学习机的短期负荷预测\差分进化算法的改进及其应用研究.caj, 226373 , 2019-01-10
基于改进差分进化算法优化极限学习机的短期负荷预测, 0 , 2019-01-13

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