针对多层前馈网络的误差反传算法存在的收敛速度慢，且易陷入局部极小的缺点，提出了采用微粒群算法（PSO）训练多层前馈网络权值的方法。

The particle swarm optimization(PSO) algorithm, is used to train neural network to solve the drawbacks of BP algorithms which is local minimum and slow convergence.

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其次，从误差反传算法在预测中存在的问题入手，提出一种混合训练算法。

Secondly, the hybrid training algorithm is proposed on the base of the Error Back-propagation algorithm's disadvantage analysis in the paper.

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其次，从误差反传算法在预测中存在的问题入手，提出一种混合训练算法。

Secondly, the hybrid training algorithm is proposed on the base of the Error Back-propagation algorithm's disadvantage analysis in the paper.

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