It is used modified BP algorithm to train ANN, and analyze topology of ANN and ways how to select its train parameters.

采用改进的BP算法来训练神经网络，并对网络的拓扑结构及其训练参数的选择进行了分析。

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In order to reduce the operation cost and optimize the unit commitment, the fast algorithm about unit commitment based on revised BP ANN (Artificial Neural Network) and dynamic search is discussed.

为了使机组达到最优组合，减少运行成本，研究了基于修正BP人工神经网络与动态搜索的快速算法在机组组合中的运用。

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The application of the improved BP algorithm, paralysis which may happen in the training procedure of ANN, was effectively avoided.

同时使用改进的BP算法，避免了神经网络学习中可能产生的麻痹现象。

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