期刊论文详细信息
Proceedings | |
Optimal Missing Value Estimation Algorithm for Groundwater Levels | |
Kenda, Klemen1  MladeniÄ, Dunja2  Koprivec, Filip3  | |
[1] Artificial Intelligence Laboratory, Jožef Stefan Institute, Ljubljana 1000, Slovenia;Author to whom correspondence should be addressed.;Jožef Stefan International Postgraduate School, Ljubljana 1000, Slovenia | |
关键词: missing values; data cleaning; data fusion; sensor fusion; machine learning; ensembles; | |
DOI : 10.3390/proceedings2110698 | |
学科分类:社会科学、人文和艺术(综合) | |
来源: mdpi | |
【 摘 要 】
In this study an algorithm for missing data imputation is presented. The algorithm uses measurements from neighboring sensors to estimate the missing values. Data-driven approach is used and methodology chooses the optimal available combination of modeling algorithm and available measurements to produce an estimate from the model with lowest error. The methodology was tested on Ljubljana polje aquifer data and has produced close to perfect results.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201910259678009ZK.pdf | 429KB | download |