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- W4382288907 abstract "In the present-day market, the use of various cryptocurrencies is getting popular, and out of them, Bitcoin is very much accepted by the user. It is an application of blockchain that is based on decentralized peer-to-peer technology that leads to the development of cryptocurrency. As it is highly volatile, there is a necessity for the proper prediction of the price of Bitcoin for the users. Existing studies indicate a good number of articles on the price prediction of Bitcoin with higher accuracy using various methodologies. This study aims to extend research work based on effective as well as efficient models to predict Bitcoin prices using other machine learning and deep learning techniques. Various machine learning models such as Facebook’s prophet, Linear regression, Autoregressive Integrated Moving Average (ARIMA), random forest, support vector regression (SVR), and deep learning model long short-term memory (LSTM) have been considered in this study for effective price prediction of Bitcoin. Later, the performance of various techniques is critically assessed using several standard parameters." @default.
- W4382288907 created "2023-06-28" @default.
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- W4382288907 date "2023-01-01" @default.
- W4382288907 modified "2023-09-25" @default.
- W4382288907 title "Bitcoin Price Prediction by Applying Machine Learning Approaches" @default.
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- W4382288907 doi "https://doi.org/10.1007/978-981-99-1203-2_26" @default.
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