Bitcoin is a decentralized digital currency that is completely virtual. It is not managed by a government or a bank. It's a digital file that can be shared from one user to the next. Bitcoin's popularity has risen in recent years, and many people have begun to invest in it. Since investment on bitcoin is increasing day to day and the bitcoin price fluctuates frequently, traders need a way to predict its price in prior so that the risks associated with it can be reduced and capital gain can be improved. The various existing works on price prediction have low accuracy and predict short term price only. Due to the difficulty of determining the exact existence of a Time Series model, it is difficult to generate appropriate forecasts. The Proposed technique uses deep learning to predict bitcoin prices with Recurrent Neural Network model using the time series data to provide the better accuracy. The novelty of work is to obtain a long-term prediction, the recurrent neural network model is trained and tested on the available dataset. This work predicts the value of bitcoin for the year 2021. When compared with other machine learning algorithms like Random Forest, Gaussian Naïve Bayes, Support Vector Machine, K-Nearest Neighbors algorithms the proposed work shows improved accuracy of 76.99% using RNN model.
Prediction of Bitcoin Price using Deep Learning Model
2021-12-02
884979 byte
Conference paper
Electronic Resource
English
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