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Application of Back-Propagation Neural Network in Horoscope Prediction

Usha Sharma, Sanjeev Karmakar, Navita Shrivastava. Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Usha Sharma, Sanjeev Karmakar, Navita Shrivastava
10.5120/ijais2016451575
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  1. Usha Sharma, Sanjeev Karmakar and Navita Shrivastava. Application of Back-Propagation Neural Network in Horoscope Prediction. International Journal of Applied Information Systems 11(2):8-15, July 2016. URL, DOI BibTeX

    @article{10.5120/ijais2016451575,
    	author = "Usha Sharma and Sanjeev Karmakar and Navita Shrivastava",
    	title = "Application of Back-Propagation Neural Network in Horoscope Prediction",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "July 2016",
    	volume = 11,
    	number = 2,
    	month = "Jul",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "8-15",
    	numpages = 8,
    	url = "http://www.ijais.org/archives/volume11/number2/906-2016451575",
    	doi = "10.5120/ijais2016451575",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

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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Keywords

Neural Network, Prediction, Back-propagation, Horoscope