Journal ArticleDOI
RETRACTED: Wind turbine power coefficient estimation by soft computing methodologies: Comparative study
Shahaboddin Shamshirband,Dalibor Petković,Hadi Saboohi,Nor Badrul Anuar,Irum Inayat,Shatirah Akib,Žarko Ćojbašić,Vlastimir Nikolić,Miss Laiha Mat Kiah,Abdullah Gani +9 more
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This article is published in Energy Conversion and Management.The article was published on 2014-05-01. It has received 53 citations till now. The article focuses on the topics: Soft computing & Turbine.read more
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Solar photovoltaic generation forecasting methods: A review
TL;DR: In this article, an extensive review on recent advancements in the field of solar photovoltaic power forecasting is presented, which aims to analyze and compare various methods of solar PV power forecasting in terms of characteristics and performance.
Journal ArticleDOI
A support vector machine–firefly algorithm-based model for global solar radiation prediction
Lanre Olatomiwa,Lanre Olatomiwa,Saad Mekhilef,Shahaboddin Shamshirband,Kasra Mohammadi,Dalibor Petković,Ch. Sudheer +6 more
TL;DR: In this article, a hybrid machine learning technique for solar radiation prediction based on some meteorological data is examined, which is developed by hybridizing the Support Vector Machines (SVMs) with Firefly Algorithm (FFA) to predict the monthly mean horizontal global solar radiation using three meteorological parameters of sunshine duration (n¯), maximum temperature (Tmax), and minimum temperature(Tmin) as inputs.
Journal ArticleDOI
A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation
Kasra Mohammadi,Shahaboddin Shamshirband,Chong Wen Tong,Muhammad Arif,Dalibor Petković,Sudheer Ch +5 more
TL;DR: 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 for both daily and monthly mean scales for an Iranian coastal city.
Journal ArticleDOI
Support vector regression based prediction of global solar radiation on a horizontal surface
Kasra Mohammadi,Shahaboddin Shamshirband,Mohammad Hossein Anisi,Khubaib Amjad Alam,Dalibor Petković +4 more
TL;DR: In this article, support vector regression (SVR) was adopted to estimate the horizontal global solar radiation (HGSR) based upon sunshine hours and maximum possible sunshine hours (N ) as input parameters.
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Potential of radial basis function based support vector regression for global solar radiation prediction
TL;DR: Experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the proposed approach and comparing SVR_rbf results with SVR, ANFIS, and ANN reveals that SVR-rbf outperforms the POLY model in terms of prediction accuracy.
References
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Support Vector Regression
TL;DR: An attempt has been made to review the existing theory, methods, recent developments and scopes of Support Vector Regression.
Journal ArticleDOI
Travel-time prediction with support vector regression
TL;DR: The feasibility of applying SVR in travel-time prediction is demonstrated and it is proved that SVR is applicable and performs well for traffic data analysis.
Proceedings ArticleDOI
Spectral feature selection for supervised and unsupervised learning
Zheng Zhao,Huan Liu +1 more
TL;DR: This work exploits intrinsic properties underlying supervised and unsupervised feature selection algorithms, and proposes a unified framework for feature selection based on spectral graph theory, and shows that existing powerful algorithms such as ReliefF and Laplacian Score are special cases of the proposed framework.
Journal ArticleDOI
Sentiment classification of online reviews to travel destinations by supervised machine learning approaches
Qiang Ye,Ziqiong Zhang,Rob Law +2 more
TL;DR: This research compared three supervised machine learning algorithms of Naive Bayes, SVM and the character based N-gram model for sentiment classification of the reviews on travel blogs for seven popular travel destinations in the US and Europe.
Proceedings ArticleDOI
Neural network based sensorless maximum wind energy capture with compensated power coefficient
Hui Li,K.L. Shi,P. G. McLaren +2 more
TL;DR: In this paper, a small wind generation system where neural network principles are applied for wind speed estimation and robust maximum wind power extraction control against potential drift of wind turbine power coefficient curve is described.