Open AccessApplication of machine learning approaches in predicting estuarine dissolved oxygen (DO) under a limited data environment
Author(s) -
M. A. Z. Siddik
Publication year - 2022
Publication title -
water quality research journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 44
eISSN - 2408-9443
pISSN - 1201-3080
DOI - 10.2166/wqrj.2022.002
Subject(s) - random forest , support vector machine , decision tree , nutrient , water quality , environmental science , computer science , estuary , data set , machine learning , linear regression , salinity , artificial intelligence , ecology , biology
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