WIND ENERGY FORECASTING USING RADIAL BASIS FUNCTION NEURAL NETWORKS

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Wind Energy Forecasting Using Radial Basis Function Neural Networks

Wind power forecast is essential for a wind farm developer for comprehensive assessment of wind potential at a particular site or topographical location. Wind energy potential at any given location is a non –linear function of mean average wind speed, vertical wind profile, energy pattern factor, peak wind speed, prevailing wind direction, lull hours, air density and a few other parameters. Win...

متن کامل

Long-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks

Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy...

متن کامل

Improved streamflow forecasting using self-organizing radial basis function artificial neural networks

Streamflow forecasting has always been a challenging task for water resources engineers and managers and a major component of water resources system control. In this study, we explore the applicability of a Self Organizing Radial Basis (SORB) function to one-step ahead forecasting of daily streamflow. SORB uses a Gaussian Radial Basis Function architecture in conjunction with the Self-Organizin...

متن کامل

Forecasting Helianthus annuus Seed Quality Based on Soil Chemical Properties Using Radial Basis Function Neural Networks

Forecasting crop chemical characteristics based on soil properties is not only a possible way to spare supplementary sampling and testing, but also a potential method of instructing cultivation planning based on regional soil surveys. In this paper, taking the data of regional agricultural geological survey on Helianthus annuus sources in the western part of the Jilin province as an attempt, ra...

متن کامل

Long-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks

Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy fac...

متن کامل

ذخیره 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: International Journal of Research in Engineering and Technology

سال: 2015

ISSN: 2321-7308,2319-1163

DOI: 10.15623/ijret.2015.0412054