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A novel integrated approach to predict bitcoin price using LSTM of RNN, GBDT and gated recurrent unit architecture

Publication Type : Journal Article

Source : International Journal of Advanced Science and Technology

Url : http://sersc.org/journals/index.php/IJAST/article/view/12393

Campus : Amaravati

School : School of Engineering

Department : Computer Science and Engineering

Year : 2020

Abstract : In this paper, we predict the Bitcoin value by allowing for all the essential considerations that affects its price. Our Contribution is to calculate the Bitcoin price with utmost probable correctness. Based on chronological value as input data of the classification, we evaluate the Bitcoin price for numerous period of future. It also imposes an stockholder to acquire added revenues by foretelling Bitcoin price for enduring period. According to current marketplace exploration and marketplace capitalization will be premeditated with this price. It is a key digital store of value. As per the fundamental details of Bitcoin are designated in depth in cited papers.

Cite this Research Publication : S. Kranthi Kumar, B. Thulasi, "A novel integrated approach to predict bitcoin price using LSTM of RNN, GBDT and gated recurrent unit architecture "International Journal of Advanced Science and Technology, Vol. 29 No. 3 (2020)

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