Browsing by Author "Ayegba, P."

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    A Prediction Model for Bitcoin Cryptocurrency Prices
    (Springer, Cham, 2022-04-20) Aorowolo, M. O.; Ayegba, P.; Yusuff, S. R.; Misra, S
    Cryptocurrencies like Bitcoin are a contentious and difficult technological innovation in today's financial system. With huge improvements in financial markets, machine learning and Artificial Intelligence aided trading have piqued interest in recent years. This study suggests a predicting model for blockchain bitcoin cryptocurrency prices and its profitability trading strategies using machine learning algorithms (ICA-Firefly and SVMs). For the prediction analysis of Bitcoin cryptocurrency data, this study combines ICA-Firefly with SVM algorithms. The model was tested on a large dataset of 2,194 samples, and its performance was analyzed in terms of evaluation metrics. In evaluation to state of the art, the ICAFirefly with L-SVM and Sigmoid SVM classification approach performs well on the bitcoin sample dataset, with an accuracy of 95% and 97%, respectively. The ICA-Firefly with the SVM model can be adopted as a viable financial system sustainability management strategy.