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The particle size distribution (PSD) plays an important role in environmental pollution detection and human health protection, such as fog, haze and soot. In this study, the Attractive and Repulsive Particle Swarm Optimization (ARPSO) algorithm and the basic PSO were applied to retrieve the PSD. The spectral extinction technique coupled with the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law were employed to investigate the retrieval of the PSD. Three commonly used monomodal PSDs, i.e. the Rosin-Rammer (R-R) distribution, the normal (N-N) distribution, the logarithmic normal (L-N) distribution were studied in the dependent model. Then, an optimal wavelengths selection algorithm was proposed. To study the accuracy and robustness of the inverse results, some characteristic parameters were employed. The research revealed that the ARPSO showed more accurate and faster convergence rate than the basic PSO, even with random measurement error. Moreover, the investigation also demonstrated that the inverse results of four incident laser wavelengths showed more accurate and robust than those of two wavelengths. The research also found that if increasing the interval of the selected incident laser wavelengths, inverse results would show more accurate, even in the presence of random error.
PAPER REVISED: 2014-06-08
PAPER ACCEPTED: 2014-07-30
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THERMAL SCIENCE YEAR 2015, VOLUME 19, ISSUE Issue 6, PAGES [2151 - 2160]
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