ITM Web Conf.
Volume 37, 2021International Conference on Innovative Technology for Sustainable Development (ICITSD-2021)
|Number of page(s)||7|
|Section||Innovative Technology for Sustainable Development|
|Published online||17 March 2021|
Block Mining reward prediction with Polynomial Regression, Long short-term memory, and Prophet API for Ethereum blockchain miners
School of Computing, SASTRA Deemed University, Tamil Nadu.
2 School of Computing, SASTRA Deemed University, Tamil Nadu.
* Corresponding author: email@example.com
The Ethereum blockchain is an open-source, decentralized blockchain with functions triggered by smart contract and has voluminous real-time data for analysis using machine learning and deep learning algorithms. Ether is the cryptocurrency of the Ethereum blockchain. Ethereum virtual machine is used to run Turing complete scripts. The data set concerning a block in the Ethereum blockchain with a block number, timestamp, crypto address of the miner, and the block rewards for the miner are explored for K means clustering for clustering miners with a unique crypto address and their rewards. Linear regression and polynomial regression are used for the prediction of the next block reward to the miner. The Long ShortTerm Memory (LSTM) algorithm is used to exploit the Ether market data set for predicting the next ether price in the market. Every kind of price and volume for every four hours is taken for prediction. The root mean square error of 34.9% is obtained for linear regression, the silhouette score is 71% for K-means clustering of miners with same rewards, with the optimal number of clusters obtained by Gap statistic method.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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