Bitcoin Cost Prediction using Deep Neural Network Technique

Authors(4) :-Kalpanasonika R, Sayasri S M, Vinothini A, Suga Priya H

The accusative of this paper is to predict the bitcoin price accurately by taking various parameters into consideration which affects the bitcoin value. Here multi-layer perceptron algorithms under deep learning are used to predict the price of crypto-currency. Many researchers have analysed the crypto-currency features in many ways such as, market price prediction, the impact of cryptocurrency in real life. It has the ability to make long-term prediction of the exchange price in crypto-currencies particularly in US dollar, based on historical trends. The bitcoin cost prediction is done based on the data set which consists of 13 features relating to the crypto-currency price recorded daily over the period of particular range.

Authors and Affiliations

Kalpanasonika R
Assistant Professor, Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore Tamil Nadu, India
Sayasri S M
BE, Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore Tamil Nadu, India
Vinothini A
BE, Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore Tamil Nadu, India
Suga Priya H
BE, Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore Tamil Nadu, India

Bitcoin Cost Prediction, Neural Network Technique, Multi-Layer Perceptron, Crypto-Currencies, Artificial Neural Network, NMC

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 96-101
Manuscript Number : CSEIT19521
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kalpanasonika R, Sayasri S M, Vinothini A, Suga Priya H, "Bitcoin Cost Prediction using Deep Neural Network Technique", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.96-101, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT19521
Journal URL : http://ijsrcseit.com/CSEIT19521

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