Researchers from China have developed a refined LSTM model using FECA and CEEMDAN-VMD decomposition to enhance water quality forecasts. By separating high-frequency noise from trends, the model significantly lowers error metrics. For instance, dissolved oxygen predictions show notable improvement, illustrating its potential for advanced environmental monitoring.