Online price forecasting model using artificial intelligence for cryptocurrencies as Bitcoin, Ethereum and Ripple
| Autor: | Melike Şişeci Çeşmeli, İhsan Pençe, Furkan Atlan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Estimation
Cryptocurrency 021103 operations research Artificial neural network Computer science business.industry 05 social sciences Ripple 0211 other engineering and technologies Price estimation Cryptography 02 engineering and technology 0502 economics and business Artificial intelligence business 050205 econometrics |
| Zdroj: | SIU |
| DOI: | 10.1109/siu49456.2020.9302082 |
| Popis: | In this study, a web model which provides price estimation in terms of Turkish Lira for Bitcoin, Ethereum and Ripple which are popular cryptocurrencies, is developed. Using the relevant model, the price estimation of these three crypto currencies between 21.09.2019 and 20.11.2019 is carried out on the web with dynamic data. Artificial intelligence methods such as adaptive neural fuzzy inference system, artificial neural networks, polynomial curve fitting and long short-term memory are used for price estimation. The aim of this study is to provide periodic forecasts to individuals or institutions interested in cryptocurrencies and to test the success of the exemplary model of the use of artificial intelligence in finance. When the forecastings that haven’t yet been realized at the relevant dates and the actual values are compared, the successful results show that the model is well established. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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