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Forecasting and Analysis of Yamuna River Water Quality

Using Hybrid AI Techniques for Environmental Monitoring

DeepCognix Environmental Team Jan 10, 2025 10 mins 2,866 views

Forecasting and Analysis of Yamuna River Water Quality

This research presents a comprehensive approach to water quality forecasting using hybrid AI techniques. The study focuses on the Yamuna River and demonstrates significant improvements in environmental monitoring capabilities.

Overview

This research presents a comprehensive approach to water quality forecasting using hybrid AI techniques, focusing on the Yamuna River.

The Challenge

Monitoring and forecasting river water quality involves complex, non-linear temporal patterns across many parameters.

Our Solution

A CNN-LSTM hybrid model captures both spatial and temporal features, optimised with feature selection and a water quality index.

Results

The model achieved 94.2% BOD prediction accuracy and 96.1% pH level forecasting accuracy.

CNN-LSTM Water Quality Environmental Monitoring Time Series Forecasting

94.2%

Peak Accuracy

Key Results

BOD Prediction Accuracy 94.2%
COD Prediction Accuracy 92.8%
pH Level Forecasting 96.1%

Techniques

CNN-LSTM Hybrid Time Series Analysis Feature Optimization Water Quality Index