Improving short-term water demand forecasting with development of dynamic neural network models considering environmental and sociocultural features

Key Points

• Improved water demand forecasting leads to more efficient water resource management, and supports sustainability efforts.
• The study shows a 15% increase in forecasting accuracy due to the use of dynamic neural networks.
• Analysis incorporates both environmental and sociocultural features to enhance predictive modeling strategies.
• These findings highlight the importance of considering diverse factors in forecasting models for better outcomes.