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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Utilizing Machine Learning and Deep Neural Network Model for Crypto Currency Price Prediction |
| Authors Name: | Mayank Chaudhary , Anant Kumar Jayswal |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_195803
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| Published Paper Id: | IJNRD2305636 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | For several decades now, the accurate and precise forecasting of the values of crypto currency index values has been a significant topic of study. In this paper, we present a hybrid modeling strategy based on two parameters which are moment correlation coefficient and root mean square error (RMSE) for predicting crypto currency prices by constructing deep learning and machine learning based models which are multivariate linear regression, MARS, artificial neural network (ANN), random forest, support vector machine (SVM), bootstrap aggregation, decision tree, extreme gradient boosting (XG Boost) and long short term memory (LSTM). We utilized the crypto index data from the online crypto currency exchange from April 1, 2021, to March 31, 2023, pertaining to the analysis we're doing. With the assistance of the training data, which included crypto index records from April 1, 2021, to December 31, 2022, we created eight regression models. Using these models, we forecasted the crypto index open values across the time frame from January 01, 2023, to March 31, 2023, and found that the Long Short Term Memory (LSTM) model was the most precise. |
| Keywords: | Crypto currency, Correlation, RMSE, Multivariate Linear Regression, MARS, ANN, Random Forest, SVM, Bootstrap Aggregation, Decision Tree, XG Boost, LSTM, crypto index. |
| Cite Article: | "Utilizing Machine Learning and Deep Neural Network Model for Crypto Currency Price Prediction", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.g296-g300, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305636.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305636 Registration ID: 195803 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: g296-g300 Country: Ghaziabad, Uttar Pradesh, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305636 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305636 |
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