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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM21550
Volume:
7 |
5 |
May 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The proposed system describes a cryptocurrency rate prediction system using Long Short- Term Memory (LSTM) neural networks. Cryptocurrency has gained Widespread acceptance in recent years, and predicting the rate of cryptocurrencies Is crucial for investors to make informed decisions. LSTM networks have been Widely used in time-series prediction tasks due to their ability to handle long-term Dependencies. The proposed system aims to predict the future rate of a Cryptocurrency by analyzing historical data using LSTM networks. The system Uses features such as opening price, closing price, highest price, lowest price, and Trading volume to train the LSTM network. The trained model is then used to Predict the future rate of the cryptocurrency. The system is evaluated using root Mean square error (RMSE) and accuracy score metrics. The results show that the Proposed system achieves high prediction accuracy, making it a valuable tool for Investors to make informed decisions about cryptocurrency investments.
KEYWORDS
Publication Date
5/22/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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