Research on Watershed Water Quality Classification Prediction Based on WOA-CNN-GRU Model

Abstract

River water quality monitoring plays a crucial role in water environment protection and management. This paper aims to explore and innovatively propose an efficient and accurate water quality classification prediction model WOA-CNN-GRU composite model. By ingeniously integrating WOA, GRU, and CNN, this model conducts comprehensive predictive research on the complex and dynamic water quality environments of the Yellow River basins in China. Addressing limitations of traditional water quality prediction methods such as single-model approaches, inadequate data processing capabilities, and limited prediction accuracy, the WOA-CNN-GRU model constructed in this study integrates core technologies from different algorithms to achieve comprehensive analysis and efficient handling of water quality data.