THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

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Ze-Ji Yi

,

Xiao-Hua Yang

,

Yu-Qi Li

A WATER QUALITY PREDICTION MODEL FOR LARGE-SCALE RIVERS BASED ON PROJECTION PURSUIT REGRESSION IN THE YANGTZE RIVER

ABSTRACT
In recent decades, the Yangtze River Basin, which carries hundreds of millions of people and a substantial economic scale, has been plagued by water quality deterioration, threatening considerably sustainable development. In this paper, a sample set is established based on the water quality indexes of chemical oxygen demand and dissolved oxygen obtained by week-by-week monitoring on the main stream of the Yangtze River in Panzhihua, Yueyang, Jiujiang, and Nanjing from 2006 to 2018. The twelve characteristic variables are selected by random forest technique, and the week-by-week dynamic prediction models of chemical oxygen demand and dissolved oxygen at each section of main stream are established by the projection pursuit regression, which can effectively predict the water quality dynamics of the Yangtze River main stream.
KEYWORDS
water quality, dynamic prediction model, random forest, projection pursuit regression, Yangtze River
PAPER SUBMITTED: 2020-03-01
PAPER REVISED: 2021-08-10
PAPER ACCEPTED: 2021-08-10
PUBLISHED ONLINE: 2022-07-16
DOI REFERENCE: https://doi.org/10.2298/TSCI2203561Y
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2022, VOLUME 26, ISSUE Issue 3, PAGES [2561 - 2567]
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A water quality prediction model for large-scale rivers based on projection pursuit regression in the Yangtze River

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence