DEVELOPING A WATER QUALITY ESTIMATION MODEL BY INTEGRATING DEEP LEARNING WITH NONLINEAR TIME-SERIES ANALYSIS

This study developed an autoregression-driven deep neural network model using deep learning techniques and nonlinear time-series analysis to estimate water quality variations in coastal areas. This local prediction model analyzes the autoregression characteristics of the nonlinear water quality system combined with an extrinsic deep learning model to express the relationship between water quality items and external factors such as tides and weather.