ADVANCED WATER QUALITY ASSESSMENT USING DEEP LEARNING

This study explores a novel approach to water quality analysis by combining deep learning and machine learning techniques. Through the utilization of convolutional neural networks (CNNs) and traditional machine learning algorithms, we aim to predict and assess water quality parameters such as [specific parameters]. The research leverages a rich dataset comprising [details on data sources] to train and validate the models. Results demonstrate the effectiveness of deep learning in capturing intricate patterns, while machine learning algorithms contribute to interpretability and generalization. The integration of these technologies provides a robust framework for comprehensive water quality assessment, facilitating timely and accurate decision-making in environmental management.