ACM Computing Surveys (CSUR)
Data mining: concepts and techniques
Data mining: concepts and techniques
Environmental Modelling & Software
Environmental Modelling & Software
Mathematics and Computers in Simulation
A comparative study of efficient initialization methods for the k-means clustering algorithm
Expert Systems with Applications: An International Journal
Position paper: Characterising performance of environmental models
Environmental Modelling & Software
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A procedure for modelling the distribution of solar spectral irradiance is proposed. It uses both statistical and data mining techniques. As a result, it is possible to simulate solar spectral irradiance distribution using some astronomical parameters and the meteorological parameters solar irradiance, temperature and humidity. With these parameters, the average photon energy and the normalization factor, which characterise the solar spectra, are estimated. First, the Kolmogorov-Smirnov two-sample test is used to analyse and compare all measured spectra. The k-means data mining technique is subsequently used to cluster all measurements. We found that three clusters are enough to characterise all observed spectra. Finally, an artificial neural network and a multivariate linear regression are estimated to simulate the solar spectral distribution matching certain meteorological parameters. The results obtained show that over 99.98% of cumulative probability distribution functions of measured spectra are the same as simulated ones.