Wind Speed Estimation From CYGNSS Using Artificial Neural Networks
نویسندگان
چکیده
منابع مشابه
Wind Speed Prediction Using Artificial Neural Networks
A multilayered artificial neural network has been used for predicting the mean monthly wind speed in regions of Cyprus where data are not available. Data for the period 1986-1996 have been used to train a neural network, whereas data for the year 1997 were used for validation. Both learning and prediction were performed with adequate accuracy. Two network architectures of the similar type have ...
متن کاملHourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks
In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in I...
متن کاملArtificial Neural Networks for Wind Speed Prediction
Wind energy has become a main challenge of conventional relic fuel energy, chiefly with the flourishing operation of multi-megawatt sized wind turbines. Though, wind with sensible speed is not sufficiently sustainable all over to construct an inexpensive wind farm. The probable site has to be systematically investigated at least with respect to wind speed profile and air density. Modelling and ...
متن کاملForecasting of Wind Speed Using Artificial Neural Networks
Wind speed forecast is essential in wind energy conversion system and may fail to operate power plant at non optimal region if not properly forecasted. This paper focuses the short term wind speed forecasting using conventional statistical method and artificial neural networks such as back propagation network (BPN), generalized regression neural network (GRNN) and radial basis function networks...
متن کاملWind Speed and Power Prediction Using Artificial Neural Networks
Short-term wind prediction over different time steps is vital for wind farms in operation for various applications. Considering the complexity of atmospheric processes governing wind, time series models are preferred over physical models for wind prediction. Artificial neural networks (ANNs), which perform a non-linear mapping between inputs and outputs, provide an alternative approach for wind...
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: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2020
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.2968156