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Intelligent decision support system for real-time water demand management

Ponte Blanco, Borja, de la Fuente, David, Parreño, José and Pino, Raúl 2016. Intelligent decision support system for real-time water demand management. International Journal of Computational Intelligence Systems 9 (1) , pp. 168-183. 10.1080/18756891.2016.1146533

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Abstract

Environmental and demographic pressures have led to the current importance of Water Demand Management (WDM), where the concepts of efficiency and sustainability now play a key role. Water must be conveyed to where it is needed, in the right quantity, at the required pressure, and at the right time using the fewest resources. This paper shows how modern Artificial Intelligence (AI) techniques can be applied on this issue from a holistic perspective. More specifically, the multi-agent methodology has been used in order to design an Intelligent Decision Support System (IDSS) for real-time WDM. It determines the optimal pumping quantity from the storage reservoirs to the points-of-consumption in an hourly basis. This application integrates advanced forecasting techniques, such as Artificial Neural Networks (ANNs), and other components within the overall aim of minimizing WDM costs. In the tests we have performed, the system achieves a large reduction in these costs. Moreover, the multi-agent environment has demonstrated to propose an appropriate framework to tackle this issue.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Uncontrolled Keywords: Water Demand Management, Decision Support System, Multi-agent Systems, Neural Networks
Publisher: Taylor & Francis
ISSN: 1875-6891
Date of First Compliant Deposit: 7 February 2017
Date of Acceptance: 1 January 2016
Last Modified: 29 Jun 2019 08:21
URI: http://orca.cf.ac.uk/id/eprint/98145

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