Cryptocurrency Price Prediction Using Neural Networks and Deep Learning
Sumit Biswas, Mohandas V. Pawar, Sachin L. Badole, Nachiket Galande, Sunil Rathod
Abstract
This rise in cryptocurrencies' value has contributed to the decentralization of authority, lowering control amongst countries. The wide price range of digital currencies highlights the need for reliable preparation for predicting the currency's price. A new model is a situation in which this paper presents a new way of forecasting digital value for money by considering several variables, such as stock market capitalization, volume, distribution, and high-end delivery. To include training results, active LSTM networks, and an overview of long-term organizations are considered. The proposed technique is used for the benchmark data sets. The results indicate the efficiency of the forecasting of digital currency.