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An Efficient Data Analysis based Flood Forecasting System (EDAFFS)

Among natural disasters observed each year, flood represents 40% and remains one of the most important problems that many governments want to solve. Each year flood is responsible for many damages that cost a lot of money and even lot of people’s life. To reduce these damages caused, flood forecasting and warning systems which are able to alert people when a flood occurs have been built. However, most of these flood forecasting systems(FFS) are usually designed for specific regions and mostly for developed countries and are not suitable for developing countries because of climatological and environmental parameters difference. The problem of flood forecasting in developing countries could be explained in one part by the lack of meteorological stations and hydraulic stations necessary for flood forecasting systems to make predictions. Moreover, existing flood forecasting systems, have forecast accuracy problem because of constant changes of the environment and climate usually caused by anthropic factors. To face these problems, this work proposes an auto-adaptive flood forecasting system based on hydraulic models and data analysis techniques on meteorological and wireless sensors networks data to realize reliable forecast. The large number of experiments conducted show that the solutions proposed in this work performed well.

Auteur(s) : Joel TANZOUAK, Blaise Omer YENKE, Ndiouma BAME, Rene NDOUNDAM
Pages : 38-47
Année de publication : 2019
Revue : Journal International Journal of Information Technology and Computer Science(IJITCS)
N° de volume : Vol.11, No.2 (2019)
Type : Article
Mise en ligne par : BAME Ndiouma