基于SMOTE-GA-CatBoost算法的全国地表水水质分类评价

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Abstract Aiming at the problems such as the high conflict of water pollution feature space and the imbalance of water quality categories in surface water classification evaluation, Synthetic Minority Oversampling Technique (SMOTE) which was combined with Genetic Algorithms (GA) and CatBoost model that used seven water quality indexes of surface water as water quality evaluation factors were respectively employed to evaluate the water quality of major rivers and important lakes-reservoirs in the country. The results were compared with the other four improved ensemble algorithms, which showed that the SMOTE pretreatment could effectively enhance the imbalance of sample categories and increase the accuracy of CatBoost model for the classification of minority water quality samples. The genetic algorithm parameters could effectively improve the convergence speed and classification accuracy of CatBoost model and optimize the classification performance of the model. The SMOTE-GA-CatBoost model showed higher performance of water quality classification compared with the other four improved integrated classification models. The values of accuracy, precision, recall and F1 of the SMOTE-GA-CatBoost model for river water quality classification reached 97.7%, 97.8%, 96.1% and 96.9%, respectively. The value of accuracy, precision, recall and F1 for water quality classification of lakes-reservoirs water were 96.7%, 96.2%, 95.4% and 95.8%, respectively. The proposed model could be used to classify and evaluate the water quality of different water areas.

Key words： surface water water quality classification and evaluation CatBoost SMOTE genetic algorithms

Received: 04 December 2022

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X824

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	Articles by authors
	XU Ling
	JING Xiang-nan
	YANG Ying
	LI Wei-hua
	LIU Yi-xin
	YAN Guo-bing

Cite this article:

XU Ling,JING Xiang-nan,YANG Ying等. National surface water quality classification evaluation based on SMOTE-GA-CatBoost method[J]. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(7): 3848-3856.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2023/V43/I7/3848

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