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American Journal of Business and Operations Research
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Title

An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest

  Fatma M. Talaat 1 *

1  Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt
    (fatma.nada@ai.kfs.edu.eg)


Doi   :   https://doi.org/10.54216/AJBOR.080201

Received: May 11, 2022 Accepted: December 09, 2022

Abstract :

Cryptocurrency is a technology that uses an encrypted peer-to-peer network to facilitate digital barter. Bitcoin, the first and most popular cryptocurrency, is paving the way as a disruptive technology to long-standing and unchanging financial payment systems. While cryptocurrencies are unlikely to replace traditional fiat currency, they have the potential to alter how Internet-connected global markets interact with one another, removing the restrictions that exist around traditional national currencies and exchange rates. Technology advances at a breakneck pace, and a technology's success is almost entirely determined by the market it tries to improve. Cryptocurrencies have the potential to change digital trade marketplaces by enabling a fee-free trading mechanism. A SWOT analysis of Bitcoin is offered, which highlights some of the recent events and movements that may have an impact on whether Bitcoin contributes to a paradigm change in economics. Cryptocurrency is a relatively new payment option, and users are naturally drawn to it because it offers privacy. To measure the impact of cryptocurrency on the world payment system, we use a Cryptocurrency extra data – Bitcoin. The proposed algorithm uses Random Forest Algorithm for prediction. The RFPA has achieved a 0.073 MSE. The RFPA has achieved the best results as it can handle huge datasets with a lot of dimensionality. It improves the model's accuracy and eliminates the problem of overfitting. When compared to other algorithms, it takes less time to train.

Keywords :

Cryptocurrency; Bitcoin; Exchange Rates; Random Forest; Machine Learning

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Cite this Article as :
Style #
MLA Fatma M. Talaat. "An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest." American Journal of Business and Operations Research, Vol. 8, No. 2, 2022 ,PP. 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)
APA Fatma M. Talaat. (2022). An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest. Journal of American Journal of Business and Operations Research, 8 ( 2 ), 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)
Chicago Fatma M. Talaat. "An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest." Journal of American Journal of Business and Operations Research, 8 no. 2 (2022): 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)
Harvard Fatma M. Talaat. (2022). An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest. Journal of American Journal of Business and Operations Research, 8 ( 2 ), 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)
Vancouver Fatma M. Talaat. An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest. Journal of American Journal of Business and Operations Research, (2022); 8 ( 2 ): 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)
IEEE Fatma M. Talaat, An Enhanced Deep Learning Technique to Measure the Impact of Cryptocurrency on the World Payment system using Random Forest, Journal of American Journal of Business and Operations Research, Vol. 8 , No. 2 , (2022) : 08-15 (Doi   :  https://doi.org/10.54216/AJBOR.080201)