Support vector regression based prediction of global solar radiation on a horizontal surface

Mohammadi, Kasra; Shamshirband, Shahaboddin; Anisi, Mohammad Hossein; Alam, Khubaib Amjad; Petković, Dalibor

doi:10.1016/j.enconman.2014.12.015

Cited by 179 publications

(57 citation statements)

References 39 publications

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“…The MAE and RMSE values found in this study are similar to those found by other authors (Tabari et al, 2012;Mohammadi et al, 2015).The results demonstrate the ability of SVM1 models to adapt to existing conditions in Yucatán.…”

Section: Estimation Of Daily Global Solar Radiationsupporting

confidence: 80%

Assessment of reference evapotranspiration and global solar radiation in Yucatán Peninsula Mexico

Quej¹,

Hugo²

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Section: Estimation Of Daily Global Solar Radiationsupporting

confidence: 80%

Assessment of reference evapotranspiration and global solar radiation in Yucatán Peninsula Mexico

Quej¹,

Hugo²

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“…Obtained results and suggested approaches can be useful in different applications at energy conversion and production [29,30].…”

Section: Resultsmentioning

confidence: 95%

Boundary conditions on the vapor liquid interface at strong condensation

Kryukov

Levashov

2015

Heat Mass Transfer

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“…For example, Zounemat-Kermani et al [55] evaluated the capability of SVM model with four different kernel functions (linear, polynomial, sigmoid, and RBF) for forecasting daily suspended sediment concentrations and further pointed out that the RBF for SVM model was the best choice for modeling hydrological phenomena. Mohammadi et al [56] investigated the ability of two different types of SVM models based on polynomial and RBF kernel functions in forecasting the horizontal global solar radiation and found that RBF for SVM was highly competent for predicting daily horizontal global solar radiation in comparison with polynomial function. As a relatively new method, ELM exhibited strong modeling accuracy in predicting daily ET, which has been verified by previous studies for other applications, such as reference ET prediction [57] and stream-flow forecasting [39].…”

Section: Discussionmentioning

confidence: 99%

Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems

Dou

Yang

2018

Advances in Meteorology

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Remarkable progress has been made over the last decade toward characterizing the mechanisms that dominate the exchange of water vapor between the biosphere and the atmosphere. This is attributed partly to the considerable development of machine learning techniques that allow the scientific community to use these advanced tools for approximating the nonlinear processes affecting the variation of water vapor in terrestrial ecosystems. Three novel machine learning approaches, namely, group method of data handling, extreme learning machine (ELM), and adaptive neurofuzzy inference system (ANFIS), were developed to simulate and forecast the daily evapotranspiration (ET) at four different grassland sites based on the flux tower data using the eddy covariance method. These models were compared with the extensively utilized data-driven models, including artificial neural network, generalized regression neural network, and support vector machine (SVM). Moreover, the influences of internal functions on their corresponding models (SVM, ELM, and ANFIS) were investigated together. It was demonstrated that most developed models did good job of simulating and forecasting daily ET at the four sites. In addition to strengths of robustness and simplicity, the newly proposed methods achieved the estimates comparable to those of the conventional approaches and accordingly can be used as promising alternatives to traditional methods. It was further discovered that the generalization performance of the ELM, ANFIS, and SVM models strongly depended on their respective internal functions, especially for SVM.

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Support vector regression based prediction of global solar radiation on a horizontal surface

Cited by 179 publications

References 39 publications

Assessment of reference evapotranspiration and global solar radiation in Yucatán Peninsula Mexico

Assessment of reference evapotranspiration and global solar radiation in Yucatán Peninsula Mexico

Boundary conditions on the vapor liquid interface at strong condensation

Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems

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