Time Series Lag Analysis of Indicators in Sewage Treatment Process

This study examines the interrelations among key indicators in sewage treatment and develops predictive models for forecasting future trends of these indicators, focusing on the importance of time series lag. We focus on pH, Final sedimentation basin outflow (FOss), Treated Water Transparency (TWT), and Treated Water Total Nitrogen (TWTN). We analyze extensive data and establish accurate predictive models with the deep learning network using advanced statistical analysis and deep learning algorithms. Our results reveal the intrinsic connections between these indicators and confirm the high accuracy of our model in predictions.