前馈神经网络的电话号码分类

Q4 Environmental Science
S. Hayat
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引用次数: 0

摘要

提出了一种基于神经网络的电话号码分类识别方法。所使用的网络是一个单隐藏层多层感知器(MLP)分类器。它的训练是基于反向传播学习。我展示了一个前馈神经网络的训练结果,将电话号码分为四类:不同的训练数据经过预处理,然后进行测试,以区分电话号码的四类/模式,以训练FFNN。我的目标是提供该领域已发表的研究的汇总,并引起进一步的研究兴趣和努力研究确定的主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phone numbers classificationwith feed-forward neural networks
A neural network (NN)-based method for phone number classification or recognition is provided in this paper. The used network is a one-hidden-layer multilayer perceptron (MLP) classifier. Its training is based on backpropagation learning. I present the results of a Feed Forward Neural Network trained to classify phone numbers into four categories: Different training data were pre-processed and then tested to distinguish between four classes/patterns of phone numbers in order to train the FFNN. My goal is to provide a coalescence of the published research in this field and to arouse further research interest in and efforts to research the identified topics.
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来源期刊
Iranian Journal of Botany
Iranian Journal of Botany Environmental Science-Ecology
CiteScore
0.80
自引率
0.00%
发文量
0
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