Year: 2024
Type: conference-paper
Abstract: This study presents a forecasting framework for the hourly water demand of district metered areas (DMAs) based on a bidirectional long short-term memory (LSTM) model which is a participant in the Battle of Water Demand Forecasting (BWDF) during the 3rd WDSA/CCWI Joint Conference. The framework consists of three portions: raw data preprocessing, initial forecasting model establishment based on LSTM, and a correction based on weather and holiday factors. The application results in the DMAs provided by the BWDF show that the proposed framework demonstrates reasonable forecasting of water demands.
Authors: Dingtong Wang, Yanning Li, Benwei Hou, Shan Wu
Institution: Beijing University of Technology
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4402416902