Artificial Intelligence Techniques for Flood Risk Management in Urban Environments

Sayers, William ORCID: 0000-0003-1677-4409, Savić, D., Kapelan, Z. and Kellagher, R. (2014) Artificial Intelligence Techniques for Flood Risk Management in Urban Environments. Procedia Engineering, 70. pp. 1505-1512. doi:10.1016/j.proeng.2014.02.165

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Abstract

Urban flooding is estimated to cause £270 million pounds worth of damage each year in England and Wales alone. There has, therefore, been a clear need to develop improved methods of identifying intervention strategies to reduce flood risk in urban environments. This paper describes ground-work performed towards evaluating the relative suitability of several algorithms applied to multi-objective optimisation of flood risk intervention strategies in an urban drainage network. An effective methodology is described for reducing an array of return period/duration rainfall files to a minimum, and it is described how this methodology makes possible comparisons of optimisation algorithms. This work has been undertaken as part of a STREAM-IDC EngD project which is a collaborative effort between the University of Exeter, and HR Wallingford.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Flooding; Floods; Drainage; Technology; Innovation; Multi-objective; Optimisation; Optimization
Related URLs:	Repository
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Susan Turner
Date Deposited:	12 Jun 2019 15:53
Last Modified:	31 Aug 2023 08:01
URI:	https://eprints.glos.ac.uk/id/eprint/6921

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