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Full-Text Articles in Hydraulic Engineering
Towards A Neural Networks-Based Prediction Tool Devoted To Low Water-Levels Forecasting: Relevant Architecture Selection Based On Main Physical Processes, A. Coutouis, A. Johannet, S. Pistre, P. -A. Ayral, L. Cadilhac
Towards A Neural Networks-Based Prediction Tool Devoted To Low Water-Levels Forecasting: Relevant Architecture Selection Based On Main Physical Processes, A. Coutouis, A. Johannet, S. Pistre, P. -A. Ayral, L. Cadilhac
International Congress on Environmental Modelling and Software
Karst aquifers provide water resource for a large part of the Mediterranean population and water resource becomes a strategic problem during summer when population increases due to tourism. To help managers to optimize the exploitation of water, this work studies the ability of a neural network model to efficiently simulate water levels in the Cèze River, connected to a karst aquifer, few months ahead during the dry season. The neural model is based on recurrent multilayer perceptrons that learn the relations between inputs (mainly rainfall and ETP) and output (water level). After a training step using 17 years of data, …
Autoflow© - A Novel Application For Water Resource Management And Climate Change Response Using Smart Technology, Khoi Anh Nguyen, Oz Sahin, Rodney Anthony Stewart, Hong Zhang
Autoflow© - A Novel Application For Water Resource Management And Climate Change Response Using Smart Technology, Khoi Anh Nguyen, Oz Sahin, Rodney Anthony Stewart, Hong Zhang
International Congress on Environmental Modelling and Software
Urban areas are increasingly at risk from climate change, with negative impacts predicted for human health, the economy and ecosystems. These risks require responses from cities to improve their resilience. Several analysis platforms have been developed worldwide to help effectively control and response to these impacts from different angles, including water resources management, energy production and consumption management, air pollution control, or other natural resources management. To contribute to this goal, Griffith University in Australia has developed Autoflow©, a smart application for water demand analysis and carbon emission monitoring and prediction. Various advanced mathematical models have been …
Water Demand Forecasting With Autoflow© Using State-Space Approach, Khoi Anh Nguyen, Oz Sahin, Rodney Anthony Stewart, Hong Zhang
Water Demand Forecasting With Autoflow© Using State-Space Approach, Khoi Anh Nguyen, Oz Sahin, Rodney Anthony Stewart, Hong Zhang
International Congress on Environmental Modelling and Software
The authors have recently developed an intelligent application, Autoflow©, which is a powerful tool to autonomously categorise residential water consumption data into a registry of single and combined events. This tool was developed using data collected in several cities in Australia, and when applied on standalone properties, the achieved accuracy ranged from 86% and 96% in terms of number of correctly classified events. Taking advantage of the analysis results from Autoflow©, the aim of this study is to propose a short-term water demand forecasting model that not only allows water utilities to predict the overall …