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Predicting Block Mining Rewards for Ethereum Blockchain Miners using Machine Learning Algorithms and the Prophet API
Authors (Affiliation): Parag Shukla (School of Cyber Security and Digital Forensics, National Forensic Sciences University), Jay Teraiya (National Forensic Sciences University), Ravirajsinh Vaghela (School of Cyber Security & Digital Forensics, National Forensic Sciences University), Vaibhav Thoke (School of Cyber Security & Digital Forensics, National Forensic Sciences University)
Abstract:

The Research centers on the application of machine learning algorithms and the Prophet API to predict block mining rewards for Ethereum blockchain miners. Leveraging the decentralized and open-source nature of the Ethereum blockchain, we harness smart contracts and real-time data for in-depth analysis. The focus is on utilizing advanced algorithms to forecast future block rewards for individual miners. Ether, the native cryptocurrency of the Ethereum blockchain, drives transactions and serves as the primary incentive for miners. Our study specifically delves into the integration of machine learning techniques to predict the forthcoming rewards for miners based on key parameters such as block number, timestamp, and Reward. To achieve this, the project employs the Prophet API, a powerful forecasting tool, alongside other machine learning algorithms. By combining machine learning algorithms and the Prophet API, our approach enhances the accuracy and reliability of predicting block mining rewards, contributing to the broader discourse on blockchain analytics and predictive modeling.

Keywords: Blockchain technology, architecture, libraries, applications of blockchain technology in library services
Vol & Issue: Special Issue - 1 (The Proceeding of ICRBDC - 2024), February 2024