#9982. Analyzing Transaction Confirmation in Ethereum Using Machine Learning Techniques

November 2026publication date
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
JCR Q4
Abstract:
Ethereum has emerged as one of the most important cryptocurrencies in terms of the number of transactions. Given the recent growth of Ethereum, the cryptocurrency community and researchers are interested in understanding the Ethereum transactions behavior. In this work, we investigate a key aspect of Ethereum: the prediction of a transaction confirmation or failure based on its features. This is a challenging issue due to the small, but still relevant, fraction of failures in millions of recorded transactions and the complexity of the distributed mechanism to execute transactions in Ethereum. To conduct this investigation, we train machine learning models for this prediction, taking into consideration carefully balanced sets of confirmed and failed transactions.
Keywords:
blockchain; ethereum; machine learning; transaction

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