Fuzzy neural network modelling for hydrological studies
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Date
2003
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Abstract
Water resources related studies involve variables, which are highly random and uncertain in nature. Most hydrological variables exhibit a high degree of temporal and spatial variability. These studies are very essential to the mankind for providing a warning of the extreme flood or drought conditions and help to optimize the operation of systems like reservoirs and power plants etc. For better hydrological design, we need proper modelling of the system using these variables. Many approaches were suggested in the past. In this research study, a new modelling approach that uses artificial neural network and fuzzy logic concepts together is proposed for modelling hydrological problems.
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Supervisors: V Chandramouli and Anjan Dutta
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CIVIL ENGINEERING