2024
DOI: 10.1371/journal.pone.0298664
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Prediction of hydrological and water quality data based on granular-ball rough set and k-nearest neighbor analysis

Limei Dong,
Xinyu Zuo,
Yiping Xiong

Abstract: Hydrological and water quality datasets usually encompass a large number of characteristic variables, but not all of these significantly influence analytical outcomes. Therefore, by wisely selecting feature variables with rich information content and removing redundant features, it not only can the analysis efficiency be improved, but the model complexity can also be simplified. This paper considers introducing the granular-ball rough set algorithm for feature variable selection and combining it with the k-nea… Show more

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