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Flood Prediction Using Support Vector Machines (SVM)

Shi, Y; Taalab, K; Cheng, T; (2016) Flood Prediction Using Support Vector Machines (SVM). In: Proceedings of the 24th GIS Research UK (GISRUK) Conference. GIS Research UK (GISRUK): London, UK. Green open access

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Abstract

Flooding is a destructive phenomenon that can risk human life, damage homes and have huge economic impacts. To plan and implement effective mitigation strategies, it is necessary to predict when and where flooding will occur. Based on a combination of rain gauge and river discharge measurement taken from the River Don catchment, UK this study proposes a Support Vector Machine (SVM) based approach to predicting river. The purpose of this work is to show the potential of the SVM method for predicting future flood events.

Type: Proceedings paper
Title: Flood Prediction Using Support Vector Machines (SVM)
Event: The 24th GIS Research UK (GISRUK) Conference (GISRUK2016)
Location: London, UK
Dates: 30 March 2017 - 01 April 2017
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.gre.ac.uk/ach/services/events/gisruk201...
Language: English
Keywords: Flooding, Support Vector Machines, River Flow, Rainfall
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1544034
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