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Bitcoin Prediction Using Multi-Layer Perceptron Regressor, PCA, and Support Vector Regression (SVR): Prediction Using Machine Learning
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Author(s): Aatif Jamshed (ABES Engineering College, Ghaziabad, India) and Asmita Dixit (ABES Engineering College, Ghaziabad, India)
Copyright: 2022
Pages: 12
Source title:
Regulatory Aspects of Artificial Intelligence on Blockchain
Source Author(s)/Editor(s): Pardis Moslemzadeh Tehrani (University of Malaya, Malaysia)
DOI: 10.4018/978-1-7998-7927-5.ch011
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Abstract
Bitcoin has gained a tremendous amount of attention lately because of the innate nature of entering cryptographic technologies and money-related units in the fields of banking, cybersecurity, and software engineering. This chapter investigates the effect of Bayesian neural structures or networks (BNNs) with the aid of manipulating the Bitcoin process's timetable. The authors also choose the maximum extensive highlights from Blockchain records that are carefully applied to Bitcoin's marketplace hobby and use it to create templates to enhance the influential display of the new Bitcoin evaluation process. They endorse actual inspection to check and expect the Bitcoin technique, which compares the Bayesian neural network and other clean and non-direct comparison models. The exact tests show that BNN works well for undertaking the Bitcoin price schedule and explain the intense unpredictability of Bitcoin's actual rate.
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