Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model - Barzegar, Rahim; Aalami, Mohammad Taghi; Adamowski, Jan (Stochastic environmental research and risk assessment, 2020)
Keywords: Aquatic Pollution; Artificial neural networks; Chemistry and Earth Sciences; Chlorophyll; Computational Intelligence; Computer Science; Correlation coefficient; Correlation coefficients; Decision trees; Deep learning; Dissolved oxygen; Earth and Environmental Science; Earth Sciences; Electrical conductivity; Electrical resistivity; Environment; Environmental monitoring; Learning algorithms; Long short-term memory; Machine learning; Math. Appl. in Environmental Science; Neural networks; Original Paper; Oxidation; pH effects; Physics; Predictions; Probability Theory and Stochastic Processes; Regression analysis; Root-mean-square errors; Statistical analysis; Statistics for Engineering; Variables; Waste Water Technology; Water Management; Water monitoring; Water Pollution Control; Water quality; Water quality management; Water resources; Water resources management; Water temperature; Deep learning; Long short-term memory; Water quality modeling; Convolutional neural network