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http://dx.doi.org/10.14400/JDC.2020.18.11.129

Predictive Analysis of Ethereum Uncle Block using Ensemble Machine Learning Technique and Blockchain Information  

Kim, Han-Min (Business School, Sungkyunkwan University)
Publication Information
Journal of Digital Convergence / v.18, no.11, 2020 , pp. 129-136 More about this Journal
Abstract
The advantages of Blockchain present the necessity of Blockchain in various fields. However, there are several disadvantages to Blockchain. Among them, the uncle block problem is one of the problems that can greatly hinder the value and utilization of Blockchain. Although the value of Blockchain may be degraded by the uncle block problem, previous studies did not pay much attention to research on uncle block. Therefore, the purpose of this study attempts to predict the occurrence of uncle block in order to predict and prepare for the uncle block problem of Blockchain. This study verifies the validity of introducing new attributes and ensemble analysis techniques for accurate prediction of uncle block occurrence. As a research method, voting, bagging, and stacking ensemble analysis techniques were employed for Ethereum's uncle block where the uncle block problem actually occurs. We used Blockchain information of Ethereum and Bitcoin as analysis data. As a result of the study, we found that the best prediction result was presented when voting and stacking ensemble techniques were applied using only Ethereum Blockchain information. The result of this study contributes to more accurately predict the occurrence of uncle block and prepare for the uncle block problem of Blockchain.
Keywords
Uncle Block; Ethereum; Bitcoin; Blockchain Information; Machine Learning; Ensemble Technique;
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Times Cited By KSCI : 6  (Citation Analysis)
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