In this paper, a Boiler Operation Optimizing model is built by using BP ( Back - Propagation ) Neural Network.

本文引入人工神经网络之BP网络 ( Back-Propagation ),建立了锅炉的运行优化模型.

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Mould, manufacturing cycle, the n back - propagation ( BP ) neural network, the mathmatical model.

模具生产周期预测, 制造周期, 设计周期,人工神经网络BP算法.

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The NN controller is trained with evolutionary computation and back propagation.

进化算法和反向传播被用于神经网络的训练.

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BP algorithm consists of two parts: information transmission and forward error back - propagation.

BP算法由两部分组成: 信息的正向传递与误差的反向传播.

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The model used multiple stepwise regression method and back propagation method independently.

模型分别采用多元逐步回归方法和反向传播方法.

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BP ( Back Propagation ) network is used to simulate the magnetization curve of generator.

其次介绍了人工神经网络方法,用常用的BP网络模型对发电机空载特性仿真.

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Based on idea of standard back - propagation ( BP ) learning algorithm, an improved BP learning algorithm is presented.

在标准反向传播 神经 网络算法的基础上, 提出了一种改进的反向传播神经网络算法.

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Through applying an improved BP ( back propagation ) algorithm to city consume, a BP model is built.

针对城市消费预测问题, 应用一种改进的BP算法,建立了相应的BP网络 模型,并设计了基于BP神经 网络的城市消费预测系统.

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Based on gradient descent rule, the BP ( Back Propagation ) algorithm is a local optimization algorithm.

bp 算法基于梯度下降原理,是一种局部寻优算法.

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