With the recent advances in the Blockchain technology, and due to its decentralized nature, it has been a much considered approach for solving issues in the Internet of Things (IoT) sector, in particular, for IoT payment platforms. As Machine-to-Machine (M2M) payments are fundamental in the IoT economy, the development of Blockchain-based payment platforms, using cryptocurrency, is continuously increasing as it enables a pure M2M, secure and private financial transactions. Unlike traditional assets, cryptocurrencies have a higher index of volatility, which makes it essential to understand the movement of their prices, as a first step to optimize Blockchain-based M2M payment transactions.
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Titolo: | A Hybrid Model for Bitcoin Prices Prediction using Hidden Markov Models and Optimized LSTM Networks |
Autori: | |
Data di pubblicazione: | 2019 |
Abstract: | With the recent advances in the Blockchain technology, and due to its decentralized nature, it has been a much considered approach for solving issues in the Internet of Things (IoT) sector, in particular, for IoT payment platforms. As Machine-to-Machine (M2M) payments are fundamental in the IoT economy, the development of Blockchain-based payment platforms, using cryptocurrency, is continuously increasing as it enables a pure M2M, secure and private financial transactions. Unlike traditional assets, cryptocurrencies have a higher index of volatility, which makes it essential to understand the movement of their prices, as a first step to optimize Blockchain-based M2M payment transactions. |
Handle: | http://hdl.handle.net/11571/1350614 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |