反向传播神经网络在星座预测中的应用

International journal of applied information systems Pub Date : 2016-07-06 DOI:10.5120/IJAIS2016451575

Usha Sharma, S. Karmakar, Navita Shrivastava.

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引用次数: 0

摘要

本文设计了一种反向传播神经网络模型，并对其参数进行了优化，用于星座预测，以识别人的类型。人的类型是一个基于行星系统的动态系统。研究发现，反向传播神经网络能够通过学习行星数据集来预测人的类型。该模型被训练到模型误差(即均方误差)1.2864E-04，在训练和测试过程中表现优异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of Back-Propagation Neural Network in Horoscope Prediction

In this study a back-propagation neural network model is designed and its parameters are optimized for prediction of horoscope to identify a person type. Person type is a dynamic system based on the planet system. It is found that the backpropagation neural network is capable to predict the person type by learning planet dataset. The model is trained up to model error (i.e., mean square error) 1.2864E-04 and performs excellent during training and testing process.

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International journal of applied information systems

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