Gold Price Prediction using Eight Neighborhood Non Linear Cellular Automata
Pokkuluri Kiran Sree1, Y. Ramu2

1Dr P.Kiran Sreee*, Professor, Dept of CSE, Shri Vishnu Engineering College for Women, Bhimavaram.
2Prof Y.Ramu, Associate Professor, Dept of CSE, Shri Vishnu Engineering College for Women, Bhimavaram.

Manuscript received on November 16, 2019. | Revised Manuscript received on 27 November, 2019. | Manuscript published on December 10, 2019. | PP: 1711-1714 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7727129219/2019©BEIESP | DOI: 10.35940/ijitee.B7727.129219
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Abstract: Gold price prediction is pronounced as one of the dynamic problems addressed by many researchers. Several researchers have proposed various methods to predict the gold price; still there is a potential room to a new novel method with more accuracy and precise prediction. This paper proposes a supervised classifier with an Eight Neighborhood -Non Linear Cellular Automata to predict the exact gold price. The input for this proposed classifier is taken from the time series data of the last ten years in India. The classifier is trained and tested to give daily predictions to the users, which helps many investors to decide the time to buy or sell gold. This classifier is trained to process large amount of statistical data, process the business decisions listed in news articles. Based on all these parameters it predicts the gold variations in future. The accuracy of the classifier tested with standard datasets was reported as 86.7%, which is considerably better when compared with the existing literature. 
Keywords:  Cellular Automata, Deep Learning, Gold P rice
Scope of the Article: Deep Learning