Measuring Discharge Using Back-Propagation Neural Network: A Case Study on Brahmani River Basin

Dillip K. Ghose

doi:10.1007/978-981-10-7566-7_59

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Measuring Discharge Using Back-Propagation Neural Network: A Case Study on Brahmani River Basin

Dillip K. Ghose

Year: 2018 Advances in intelligent systems and computing Pages: 591-598 Publisher: Springer Nature

DOI: 10.1007/978-981-10-7566-7_59

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Keywords:

Environmental science Flood control Stream flow Surface runoff Stage (stratigraphy) Structural basin Discharge Flood myth Drainage basin Hydrology (agriculture) Monsoon Artificial neural network Meteorology Climatology Geography Computer science Geology Machine learning Cartography Ecology Geotechnical engineering

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Hydrological Forecasting Using AI

Physical Sciences → Environmental Science → Environmental Engineering

Hydrology and Watershed Management Studies

Physical Sciences → Environmental Science → Water Science and Technology

Flood Risk Assessment and Management

Physical Sciences → Environmental Science → Global and Planetary Change

Measuring Discharge Using Back-Propagation Neural Network: A Case Study on Brahmani River Basin

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