Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that prese...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00053.pdf |
| _version_ | 1797213245196468224 |
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| author | Fadhil Heba M. Makhool Noor Q. |
| author_facet | Fadhil Heba M. Makhool Noor Q. |
| author_sort | Fadhil Heba M. |
| collection | DOAJ |
| description | Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The ability of the tool in analyzing past data on historical prices combined with machine learning, orchestrate an appealing scene of predictions equipped with choices and information, users turn into the main characters in a financial discovery story conducted by the cryptocurrency system. The numerical results also support the effectiveness of the tool as highlighted by standout corresponding numbers such as lower RMSE value 150.96 for ETH and minimized normalized RMSE scaled down to under, which is. The quantitative successes underline the usefulness of this tool to give precise predictions and improve user interaction in an entertaining world of cryptocurrency investments. |
| first_indexed | 2024-04-24T10:55:13Z |
| format | Article |
| id | doaj.art-48ccedd9a95e42b3870a83649a522f8a |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-04-24T10:55:13Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-48ccedd9a95e42b3870a83649a522f8a2024-04-12T07:36:22ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01970005310.1051/bioconf/20249700053bioconf_iscku2024_00053Forecasting Cryptocurrency Market Trends with Machine Learning and Deep LearningFadhil Heba M.0Makhool Noor Q.1Department of Information and Communication, Al-Khwarizmi College of Engineering, University of BaghdadDepartment of Information and Communication, Al-Khwarizmi College of Engineering, University of BaghdadCryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The ability of the tool in analyzing past data on historical prices combined with machine learning, orchestrate an appealing scene of predictions equipped with choices and information, users turn into the main characters in a financial discovery story conducted by the cryptocurrency system. The numerical results also support the effectiveness of the tool as highlighted by standout corresponding numbers such as lower RMSE value 150.96 for ETH and minimized normalized RMSE scaled down to under, which is. The quantitative successes underline the usefulness of this tool to give precise predictions and improve user interaction in an entertaining world of cryptocurrency investments.https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00053.pdf |
| spellingShingle | Fadhil Heba M. Makhool Noor Q. Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning BIO Web of Conferences |
| title | Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning |
| title_full | Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning |
| title_fullStr | Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning |
| title_full_unstemmed | Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning |
| title_short | Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning |
| title_sort | forecasting cryptocurrency market trends with machine learning and deep learning |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/16/bioconf_iscku2024_00053.pdf |
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