Wavelet neural network model for reservoir inflow prediction
نویسندگان
چکیده
منابع مشابه
Reservoir inflow forecasting using artificial neural network
Hydrologic forecasting plays an ever increasing role in water resource management, as engineers are required to make component forecasts of natural inflows to reservoirs for numerous purposes. Resulting forecast techniques vary with the system purpose, physical characteristics, and availability of data. As most hydrological parameters are subjected to the uncertainty, a proper forecasting metho...
متن کاملReservoir Inflow Forecasting Using Neural Networks
In utilities using a mixture of hydroelectric and nonhydroelectric power, the economics of the hydroelectric plants depend upon the reservoir height and the inflow into the reservoir for several days into the future. Accurate forecasts of reservoir inflow allow the utility to feed proper amounts of fuel to individual plants, and to economically allocate the load between various non-hydroelectri...
متن کاملVerification of an Evolutionary-based Wavelet Neural Network Model for Nonlinear Function Approximation
Nonlinear function approximation is one of the most important tasks in system analysis and identification. Several models have been presented to achieve an accurate approximation on nonlinear mathematics functions. However, the majority of the models are specific to certain problems and systems. In this paper, an evolutionary-based wavelet neural network model is proposed for structure definiti...
متن کاملNanofluid Thermal Conductivity Prediction Model Based on Artificial Neural Network
Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...
متن کاملA combined Wavelet- Artificial Neural Network model and its application to the prediction of groundwater level fluctuations
Accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. Combined Wavelet-Artificial Neural Network (WANN) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. This study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientia Iranica
سال: 2012
ISSN: 1026-3098
DOI: 10.1016/j.scient.2012.10.009