Mounce, S., Shepherd, W. orcid.org/0000-0003-4434-9442, Ostojin, S. et al. (4 more authors) (2020) Optimisation of a fuzzy logic-based local real-time control system for mitigation of sewer flooding using genetic algorithms. Journal of Hydroinformatics, 22 (2). jh2019058. pp. 281-295. ISSN 1464-7141
Abstract
Urban flooding damages properties, causes economic losses and can seriously threaten public health. An innovative, fuzzy logic (FL)-based, local autonomous real-time control (RTC) approach for mitigating this hazard utilising the existing spare capacity in urban drainage networks has been developed. The default parameters for the control algorithm, which uses water level-based data, were derived based on domain expert knowledge and optimised by linking the control algorithm programmatically to a hydrodynamic sewer network model. This paper describes a novel genetic algorithm (GA) optimisation of the FL membership functions (MFs) for the developed control algorithm. In order to provide the GA with strong training and test scenarios, the compiled rainfall time series based on recorded rainfall and incorporating multiple events were used in the optimisation. Both decimal and integer GA optimisations were carried out. The integer optimisation was shown to perform better on unseen events than the decimal version with considerably reduced computational run time. The optimised FL MFs result in an average 25% decrease in the flood volume compared to those selected by experts for unseen rainfall events. This distributed, autonomous control using GA optimisation offers significant benefits over traditional RTC approaches for flood risk management.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IWA Publishing. This is an author-produced version of a paper subsequently published in Journal of Hydroinformatics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | fuzzy logic; genetic algorithm; real-time control; sewer flooding; urban flood risk |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 641931 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jan 2020 12:37 |
Last Modified: | 19 Oct 2021 11:21 |
Status: | Published |
Publisher: | IWA Publishing |
Refereed: | Yes |
Identification Number: | 10.2166/hydro.2019.058 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154920 |