DEVELOPING A SMART CRYPTO-CURRENCY PRICE PREDICTION MODEL BY LEVERAGING THE MACHINE LEARNING TECHNIQUES
Tejas Thakral
Abstract
The goal of the proposed research project is to forecast cryptocurrency prices. Cryptocurrencies are digital currency that can be used as long-term investments or for a variety of transactions. The majority of current systems focus just on the Bitcoin cryptocurrency. However, cryptocurrencies other than bitcoin are also widely used. With remarkable precision, the proposed algorithm would be able to forecast the prices of all the important cryptocurrencies. A multitude of factors will be considered in order to make a reliable price prediction. The relationship between the price of cryptocurrency and the US dollar will be the primary criterion. These days, trading cryptocurrency prices is one of the most sought-after forms of exchange. The recommended technique would be very beneficial for both regular traders and investors. Facebook Prophet is the machine learning algorithm that will be used to predict these prices. Facebook Prophet predicts time series with notable speed and accuracy.
References
- Jiayun Lao, “Bitcoin Price Prediction In a time of covid 19â€, 2020 Management Science Informatization and Economic Innovation Development Conference.
- Karunya Rathan, Samorouthu Venkat Sai, Tubat i Sai, “Cryptocurrency Price Prediction using decision tree and regression techniquesâ€, Proceedings of the Third International Conference on Trends in Electronics and Informatics.
- Seçkin KARASU, Aytaç ALT AN, Zehra SARAÇ, Rıfat HACIOÄžLU, “Prediction of Bitcoin Prices with Machine Learning Methods using Time Series Dataâ€.
- Siddhi Velankar, Sakshi Valecha, Shreya Maji, “Bitcoin Price Predict ion using Machine Learningâ€, International Conference on communication technology.
- Thearasak Phaladis, Thanisa Numnonda, “Machine Learning Models Comparison for Bitcoin Price Predictionâ€.
- Grace L.K, Asha P, D. Usha Nandini, G. Kalaiarasi , “Price predict ion of bitcoinâ€.
- Prachi Vivek Rane, Sudhir N.Dhage, “Systematic erudition of bitcoin price predict ion using machine learning techniquesâ€.
- Kavitha H, Ut tam Kumar Sinha, Surbhi, “Performance evaluation of machine learning algorithms for bitcoin price predictionâ€.
- Giulia serfani, Qingquan zhang, Macro Brambilla, Jiayue wang, Yiwei hu, “Sentiment-driven price prediction of the bitcoin based on statistical and deep learning approachesâ€.
- Sean McNally, Jason Roche, Simon Caton, “Predicting the price of bitcoin using machine learningâ€.
- Leonardo Felizardo, Roberth Oliveira, Emilio del-moral Hernandez, Fabio cozman, “Comparative study of bitcoin price predict ion using Wavenets, Recurrent neural networks and other machine learning methodsâ€.
- Sakshi Tandon, Shreya Tripathi, Pragya Saraswat , Chetna Dabas, “Bitcoin price forecasting using LST M and 10-fold cross validationâ€.
- Shaomi Rahman, Jonayed nafis Hemel, Syed junayed Ahmed anta, Hossain Al muhee, Jia Uddin, “Sentiment analysis using R: An approach to correlate cryptocurrency price fluctuations with change in user sentiment using machine learningâ€.
- Guangcheng li, Qinglin Zhao, Mengfei song, Daidong du, Jianwen yuan, Xuanhui Chen, Hong liang, “Predicting global computing power of blockchain using cryptocurrency pricesâ€.
- S.Yogeshwaran, Maninder jeet Kaur, Piyush Maheshwari, “Project based learning: Predicting bitcoin prices using deep learningâ€.
- Chen, Joy Iong Zong, and P. Hengjinda, “Early Prediction of Coronary Artery Disease (CAD) by Machine Learning Method-A Comparative Studyâ€.
- Vijayakumar, T, “Posed Inverse Problem Rectification Using Novel Deep Convolutional Neural Networkâ€
Back