Hunan University of Technology and Business

Xintong Ouyang

Liang Chen

Jiayin Guo

Changqing Su

Yang Chen

Linfeng Jin

Huan Li

Shengbo Gu

Xinxing Li

Yongmei Xu

A layout optimization method of water quality monitoring points based on a RF-C-SOM clustering algorithm includes: preprocessing collected water quality data to obtain preprocessed water quality data that are used as data, and using water quality categories as labels to train a random forest model to determine feature importance of water quality indicators; selecting important features based on the feature importance and model training accuracy, performing dimensionality reduction on the preprocessed water quality data to obtain dimension-reduced data; performing a fuzzy clustering on the dimension-reduced data to obtain a water quality section classification result, and based on it, determining initial weight values of a self-organizing mapping algorithm; initializing neurons and training a self-organizing mapping network model with the initial weight values; obtaining a point clustering result through the self-organizing mapping network model; and conducting a water quality index evaluation for the point clustering result before and after screening.

Layout optimization method of water quality monitoring points based on rf-c-som clustering algorithm

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Loudi, China

Xintong Ouyang