Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji
Masters Thesis
Title | Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in Fiji |
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Type | Masters Thesis |
Authors | |
Author | Moishin, Mohammed |
Supervisor | Deo, Ravinesh C. |
Prasad, Ramendra | |
Raj, Nawin | |
Abdulla, Shahab | |
Institution of Origin | University of Southern Queensland |
Qualification Name | Master of Science (Research) |
Number of Pages | 98 |
Year | 2021 |
Digital Object Identifier (DOI) | https://doi.org/10.26192/zwww-vw94 |
Abstract | Floods are frequently occurring natural disasters that can cause significant damage to human lives, natural resources, and the civil infrastructures. The devastating impacts of flood events warrant the need to develop innovative means of both monitoring and forecasting of flood events to assist in reducing the damage caused by such events. In this research project, new mathematical methods designed to provide an objective explanation of the progression and forecasting of future flood events in Fiji are explored. Firstly, a flood monitoring tool known as the Flood Index ( |
Keywords | hydrology, flood forecasting, deep learning, flood index, artificial intelligence |
ANZSRC Field of Research 2020 | 460299. Artificial intelligence not elsewhere classified |
370799. Hydrology not elsewhere classified | |
Byline Affiliations | School of Sciences |
https://research.usq.edu.au/item/q6qx6/development-of-flood-risk-monitoring-and-forecasting-system-with-artificial-intelligence-predictive-models-for-community-risk-management-in-fiji
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