• Introduce the Error Back-Propagation algorithm.

    介绍了误差逆传播算法。

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

    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。

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  • This paper gave a brief review on neural nets and neural computers, neuron models, layered network structures, error back-propagation algorithm and its application to geophysical inversion.

    本文简要介绍神经网络与神经计算机,神经元模型,层状网络结构,误差逆传播算法及其在地球物理反演中的应用。

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  • The mathematic frame of the neural network and error back propagation algorithm were introduced.

    介绍了小波神经网络的数学框架及其误差反向学习算法。

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  • Combining wavelet analysis and neural network characteristics, the error back propagation wavelet neural network based structure and algorithm to ship roll time series prediction are given.

    结合小波分析和神经网络的特点,建立了应用于船舶横摇运动时间序列预报的误差反传小波神经网络结构并给出了算法。

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  • This paper provided the deduction of an algorithm for artificial neural network - the error back-propagation learning algorithm and the procedure to carry it out on computer.

    提供了人工神经网络的一种算法-误差反向传播算法的数学推导方法及上机实现步骤。

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  • Then the algorithm of the Tutoring positive signal propagation and error back-propagation of two processes, and in which the signal value deduction, deduction for error analysis and elaboration.

    然后对本授导算法中的信号正向传播与误差反向传播两个过程,以及其中的信号值推演、误差值推演进行了分析和阐述。

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  • The new model was based on the weight adjustments of error back propagation of BP algorithm and the weight modification using particle swarm optimization (PSO).

    提出一种基于粒子群算法优化BP网络的权值调整新方法。

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  • A one-by-one learning algorithm for multi-layer neural network modelling is presented based on the back-propagation mechanism of network error.

    基于误差反向传播的机制,针对连续制造过程的预测与控制,提出多层神经网络的逐个样本学习算法。

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  • A one-by-one learning algorithm for multi-layer neural network modelling is presented based on the back-propagation mechanism of network error.

    基于误差反向传播的机制,针对连续制造过程的预测与控制,提出多层神经网络的逐个样本学习算法。

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