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In this study, the effectiveness of six numerical methods is evaluated to determine the shape (k) and scale (c) parameters of Weibull distribution function for the purpose of calculating the wind… Expand
Most people would produce their own clean local energy if it were easy and affordable. When a renewable energy system is installed, there is an upfront cost that can be partially or completely offset… Expand
In this study, by using long-term global solar radiation data and other meteorological parameters, 11 empirical models taken from the literature were tested for prediction of monthly mean daily… Expand
In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation. The predictions are… Expand
In this paper, the accuracy of a hybrid machine learning technique for solar radiation prediction based on some meteorological data is examined. For this aim, a novel method named as SVM–FFA is… Expand
Abstract Precise information of wind speed probability distribution is truly significant for many wind energy applications. The objective of this study is to evaluate the suitability of different… Expand
Abstract In this paper, the support vector regression (SVR) methodology was adopted to estimate the horizontal global solar radiation (HGSR) based upon sunshine hours ( n ) and maximum possible… Expand
Engineering, Computer Science
The study results convincingly advocate that ELM can be employed as an efficient method to predict daily dew point temperature with much higher precision than the SVM and ANN techniques. Expand
Precise predictions of wind power density play a substantial role in determining the viability of wind energy harnessing. In fact, reliable prediction is particularly useful for operators and… Expand
Abstract This study deals with identifying whether the accuracy of the day of the year-based (DYB) models for prediction of the horizontal daily global solar radiation is as competitive as the… Expand
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