Abstract
The Mahanadi River basin is one of the biggest basins of India and serves as a lifeline for the region it passes through. However, the region often experiences an erratic rainfall and climate condition which affects the livelihoods of the people living nearby. Aiming to solve this problem, a novel approach is illustrated in this paper. Application of artificial neural network is a popular technique for prediction of various hydrological parameters as it provides fairly correct results. Here, an attempt has been made to incorporate wavelet transform in ANN, also known as wavelet artificial neural network (W-ANN), to further increase its scope and efficacy. The results were then evaluated using well-known statistical indices. It was concluded that W-ANN has better forecasting capacity than simple ANN model and it can be implemented for prediction of monthly runoff in similar basins and reservoirs.
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Sahoo, G.K., Mishra, A., Panda, D.P., Sahoo, A., Samantaray, S., Satapathy, D.P. (2023). Simulation of Monthly Runoff in Mahanadi Basin with W-ANN Approach. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_44
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DOI: https://doi.org/10.1007/978-981-19-7513-4_44
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