A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

Mohammadi, Kasra; Shamshirband, Shahaboddin; Chong, Wen Tong; Arif, Muhammad; Petković, Dalibor; Ch, Sudheer

doi:10.1016/j.enconman.2014.12.050

Cited by 235 publications

(66 citation statements)

References 64 publications

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“…Regarding the possibility of modelling the amount of solar radiation from UAV-based sensors, several studies that have been found in the literature are mainly focused on either traditional meteorological datasets [23][24][25][26][27] or combined works (point cloud analysis derived from UAV images and meteorological solar radiation datasets) [28]. The results of this study [28] verified the potential of indirect methods for estimating the amount of solar radiation, providing input to ecosystems that are dependent on solar radiation.…”

Section: Introductionsupporting

confidence: 55%

UAV Capability to Detect and Interpret Solar Radiation as a Potential Replacement Method to Hemispherical Photography

et al. 2018

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Solar radiation is one of the most significant environmental factors that regulates the rate of photosynthesis, and consequently, growth. Light intensity in the forest can vary both spatially and temporally, so precise assessment of canopy and potential solar radiation can significantly influence the success of forest management actions, for example, the establishment of natural regeneration. In this case study, we investigated the possibilities and perspectives of close-range photogrammetric approaches for modeling the amount of potential direct and diffuse solar radiation during the growing seasons (spring-summer), by comparing the performance of low-cost Unmanned Aerial Vehicle (UAV) RGB imagery vs. Hemispherical Photography (HP). Characterization of the solar environment based on hemispherical photography has already been widely used in botany and ecology for a few decades, while the UAV method is relatively new. Also, we compared the importance of several components of potential solar irradiation and their impact on the regeneration of Pinus sylvestris L. For this purpose, a circular fisheye objective was used to obtain hemispherical images to assess sky openness and direct/diffuse photosynthetically active flux density under canopy average for the growing season. Concerning the UAV, a Canopy Height Model (CHM) was constructed based on Structure from Motion (SfM) algorithms using Photoscan professional. Different layers such as potential direct and diffuse radiation, direct duration, etc., were extracted from CHM using ArcGIS 10.3.1 (Esri: California, CA, USA). A zonal statistics tool was used in order to extract the digital data in tree positions and, subsequently, the correlation between potential solar radiation layers and the number of seedlings was evaluated. The results of this study showed that there is a high relation between the two used approaches (HP and UAV) with R 2 = 0.74. Finally, potential diffuse solar radiation derived from both methods had the highest significant relation (−8.06% bias) and highest impact in the modeling of pine regeneration.

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Section: Introductionsupporting

confidence: 55%

UAV Capability to Detect and Interpret Solar Radiation as a Potential Replacement Method to Hemispherical Photography

et al. 2018

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“…Over time, the radial basis function (RBF) has been repeatedly proven to be the ideal function in its category due to its ability for efficient, simple, reliable, and adaptable computation for the purpose of optimization especially for adaptability in handling the parameters which are complex (Rajasekaran et al 2008;Yang et al 2009;Wu and Wang 2009). Only the solution of a set of linear functions are required for the training of RBF kernel equation rather than the lengthy and complicated demanding quadratic programming problem Mohammadi et al 2015c). Accordingly, the radial basis equation with parameter σ is adopted.…”

Section: Svmmentioning

confidence: 99%

RETRACTED ARTICLE: A hybrid SVM-FFA method for prediction of monthly mean global solar radiation

Shamshirband

Mohammadi

Chong

et al. 2015

Theor Appl Climatol

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In this study, a hybrid support vector machine-firefly optimization algorithm (SVM-FFA) model is proposed to estimate monthly mean horizontal global solar radiation (HGSR). The merit of SVM-FFA is assessed statistically by comparing its performance with three previously used approaches. Using each approach and long-term measured HGSR, three models are calibrated by considering different sets of meteorological parameters measured for Bandar Abbass situated in Iran. It is found that the model (3) utilizing the combination of relative sunshine duration, difference between maximum and minimum temperatures, relative humidity, water vapor pressure, average temperature, and extraterrestrial solar radiation shows superior performance based upon all approaches. Moreover, the extraterrestrial radiation is introduced as a significant parameter to accurately estimate the global solar radiation. The survey results reveal that the developed SVM-FFA approach is greatly capable to provide favorable predictions with significantly higher precision than other examined techniques. For the SVM-FFA (3), the statistical indicators of mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and coefficient of determination (R 2 ) are 3.3252 %, 0.1859 kWh/m 2 , 3.7350 %, and 0.9737, respectively which according to the RRMSE has an excellent performance. As a more evaluation of SVM-FFA (3), the ratio of estimated to measured values is computed and found that 47 out of 48 months considered as testing data fall between 0.90 and 1.10. Also, by performing a further verification, it is concluded that SVM-FFA (3) offers absolute superiority over the empirical models using relatively similar input parameters. In a nutshell, the hybrid SVM-FFA approach would be considered highly efficient to estimate the HGSR.

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“…Although attempting to model natural phenomena has a long history, the recent application of nature inspired algorithms like firefly algorithm [6], neuro fuzzy technique [7] and genetic programming [8] in the area of soft computing and also recent improvements in forecasting approaches [9,10], has lead to more accurate analysis and predictions, and thereby causing a noticeable growth of interest in this field [11][12][13][14][15][16][17][18]. However, attempts at improving signal extraction and forecasting using bio-inspired algorithms is a relatively new area of research.…”

Section: Introductionmentioning

confidence: 99%

From nature to maths: Improving forecasting performance in subspace-based methods using genetics Colonial Theory

Hassani

Ghodsi

Silva

et al. 2016

Digital Signal Processing

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Many scientific fields consider accurate and reliable forecasting methods as important decision-making tools in the modern age amidst increasing volatility and uncertainty. As such there exists an opportune demand for theoretical developments which can result in more accurate forecasts. Inspired by Colonial Theory, this paper seeks to bring about considerable improvements to the field of time series analysis and forecasting by identifying certain core characteristics of Colonial Theory which are subsequently exploited in introducing a novel approach for the grouping step of subspace based methods. The proposed algorithm shows promising results in terms of improved performances in noise filtering and forecasting of time series. The reliability and validity of the proposed algorithm is evaluated and compared with popular forecasting models with the results being thoroughly evaluated for statistical significance and thereby adding more confidence and value to the findings of this research.

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A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

Cited by 235 publications

References 64 publications

UAV Capability to Detect and Interpret Solar Radiation as a Potential Replacement Method to Hemispherical Photography

UAV Capability to Detect and Interpret Solar Radiation as a Potential Replacement Method to Hemispherical Photography

RETRACTED ARTICLE: A hybrid SVM-FFA method for prediction of monthly mean global solar radiation

From nature to maths: Improving forecasting performance in subspace-based methods using genetics Colonial Theory

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