A Review on Flood Prediction Algorithms and A Deep Neural Network Model for Estimation of Flood Occurrence

Author:

Ullah Tabassum Farhana,O.S. Gnana Prakasi,P Kanmani

Abstract

Flood occurs as often as possible happens due to many environmental changes in our planet in the present years. The occurrence and damages caused by flood is very high. Major cause of flood is due to heavy rainfall which in turn increases the water level of the rivers and other water bodies. The various factors that play a major role in the occurrence of rainfall are rise in temperature, humidity level, dew point, pressure in and around the area of concern, wind speed, etc. In order to reduce the number of victims due to flood it is necessary to have a system to predict flood occurrence. In this paper, we classify and analyzed the various prediction algorithms which show usage of Deep Neural Network produces better results. In addition, a design model has been proposed to predict the flood by training the Deep Neural Network with the above-mentioned factors.

Publisher

Asian Research Association

Subject

General Earth and Planetary Sciences,General Environmental Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Flood prediction through hydrological modeling of rainfall using Conv1D-SBiGRU algorithm and RDI estimation: A hybrid approach;Stochastic Environmental Research and Risk Assessment;2024-07-20

2. An Intelligent Flood Forecasting System Using Artificial Neural Network in WSN;Proceedings of Second Doctoral Symposium on Computational Intelligence;2021-09-20

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