An evolutionary Multilayer Perceptron algorithm for real time river flood prediction
Conference paper
Suddul, G., Dookhitram, K., Bekaroo, G. and Shankhur, N. 2020. An evolutionary Multilayer Perceptron algorithm for real time river flood prediction. 2020 Zooming Innovation in Consumer Technologies Conference (ZINC). Novi Sad, Serbia 26 - 27 May 2020 IEEE. pp. 109-112 https://doi.org/10.1109/ZINC50678.2020.9161824
Type | Conference paper |
---|---|
Title | An evolutionary Multilayer Perceptron algorithm for real time river flood prediction |
Authors | Suddul, G., Dookhitram, K., Bekaroo, G. and Shankhur, N. |
Abstract | Severe flash flood events give very little opportunity for issuing warnings. In this paper, we approach the automated and real time prediction of river flooding by proposing and evaluating different variations of the conventional Multilayer Perceptron (MLP) machine learning algorithm. Our first approach follows a trial and error attempt to optimize the MLP architecture. The second and third approaches are based on the application of nature inspired evolutionary techniques, namely the Genetic Algorithm (MLP-GA) and the Bat Algorithm (MLP-BA) respectively. The MLP-GA generates an improved MLP configuration and MLP-BA enhances the training method. Our fourth, novel approach (MLP-BA-GA) is based on the application of GA to further optimize both the BA and MLP architecture. When compared with previous work, experiments show improvement in the accuracy of river flood prediction, with significant results for the MLP-BA-GA. |
Keywords | Artificial Neural Network; Bat Algorithm; Flood Prediction; Genetic Algorithm; Machine Learning Optimization; Metaheuristic Model; Evolutionary Computing |
Sustainable Development Goals | 11 Sustainable cities and communities |
Middlesex University Theme | Sustainability |
Conference | 2020 Zooming Innovation in Consumer Technologies Conference (ZINC) |
Page range | 109-112 |
Proceedings Title | 2020 Zooming Innovation in Consumer Technologies Conference (ZINC) |
ISBN | |
Electronic | 9781728182599 |
Paperback | 9781728182605 |
Publisher | IEEE |
Publication dates | |
Online | 07 Aug 2020 |
May 2020 | |
Publication process dates | |
Deposited | 30 Sep 2022 |
Accepted | 15 Feb 2020 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Copyright Statement | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ZINC50678.2020.9161824 |
Scopus EID | 2-s2.0-85091344598 |
Web of Science identifier | WOS:000621646700023 |
Web address (URL) of conference proceedings | https://ieeexplore.ieee.org/xpl/conhome/9152810/proceeding |
Related Output | |
Has metadata | http://www.scopus.com/inward/record.url?eid=2-s2.0-85091344598&partnerID=MN8TOARS |
Language | English |
https://repository.mdx.ac.uk/item/89zzy
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