Research on Water Resource Carrying Capacity Assessment and Water Quality Forecasting Based on Feature Selection with CNN-BiLSTM-Attention Model of the Min River Basin

Water, Год журнала: 2025, Номер 17(6), С. 824 - 824

Опубликована: Март 13, 2025

To achieve a more accurate assessment of water resource carrying capacity (WRCC), the indicators resources, social and ecological environment were selected to construct WRCC system on basis combinatorial assignment method with advantages. Moreover, incorporation key quality influences into predictions facilitated performance predictive models. Adaptive Lasso Regression was used select factors affecting quality, whereas CatBoost algorithm ranked importance by in prediction model. The Convolutional Neural Network-Bidirectional Long Short-Term Memory-Attention (CNN-BiLSTM-Attention) model forecast WQI. research results propose new evaluation method. show that average barrier levels for socio-economic development, 34.97%, 34.93%, 30.10%, respectively. Compared other layers WRCC, obstacle degree layer has always been lower. total sewage treatment, greening coverage built-up areas, per capita green space parks main within Min River Basin. Based factor screening, it can be seen dissolved oxygen is positively correlated watershed, while influencing are negatively Total nitrogen had greatest impact conditions regression coefficient −1.7532. From comparison results, known hybrid make MAE value 45% monitoring points reach minimum, RMSE 35% minimum. percentages remaining models reached lowest values 15% 20% 30%, models, MSE relatively small, which conducive predicting

Язык: Английский

Characterizing the Concentration of Ethanol-Water Solutions by Oblique-Incidence Reflectivity Difference Combined with Deep Learning Algorithms

Опубликована: Янв. 1, 2024

Язык: Английский

Characterizing the concentration of ethanol-water solutions by oblique-incidence reflectivity difference combined with deep learning algorithms

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2024, Номер 325, С. 125069 - 125069

Опубликована: Авг. 30, 2024

Язык: Английский