*2.2. The Framework of the Proposed Model*

The single neural network model is susceptible to fluctuations in the water quality time series during training, which affects the prediction accuracy. Therefore, this study introduced the signal time and frequency decomposition method for water quality data preprocessing and built a hybrid prediction model based on "decomposition- predictionreconstruction" to improve the overall prediction accuracy. The hybrid model is made up of five components:


The whole algorithm flow chart is shown in Figure 3.
