Abstract
Flood is a dangerous occurrence that results to loss of lives and properties, therefore adequate preventive measures and rules must be encouraged to reduce its menace. Different models have been developed for the prediction of floods using machine learning algorithms. This study is aimed at developing a novel model to enhance the predictive performance of the existing model using artificial neural network. ANN parameters were tuned and implemented with python 3.7 programming language on Intel (R) Core(TM) i3, 4G RAM of Windows 10 operating system. The proposed model has optimal training and validation accuracy of 98.91% and 96.54% respectively. The experimental results also showed lowest training and validation loss of 0.0240 and 0.1082 respectively.
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