提高BP神经网络泛化能力的输入值函数

T. He, Shijue Zheng, Ping Zhang, Ming Zou
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引用次数: 1

摘要

众所周知,BP神经网络有两个重要的优点和缺点:学习速度和泛化能力。本文提出了一种添加输入值函数(IVF)的新方法来提高BP神经网络的泛化能力。结果表明:该方法在一定程度上提高了气相色谱的质量。但是如果我们想要在各个领域做更多的推广,还有很多事情需要我们研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Input Values Function for Improving Generalization Capability of BP Neural Network
As is known to all, Back propagation (BP) neural network has two important advantage and disadvantage: learning speed and generalization capability (GC). In this paper, we propose a new method by adding input values function (IVF) to improve the generalization of BP neural network. The result shows: GC in a certain extent has been improved throught this method. But if we want to do much more promoting in various fields, there are still a lot of things that we must to be studied.
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