Abstract

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 back-propagation 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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