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Estimation of the particle size distribution of colloids from multiangle dynamic light scattering measurements with particle swarm optimization
摘要： In this paper particle Swarm Optimization (PSO) algorithms are applied to estimate the particle size distribution (PSD) of a colloidal system from the average PSD diameters, which are measured by multi-angle dynamic light scattering. The system is considered a nonlinear inverse problem, and for this reason the estimation procedure requires a Tikhonov regularization method. The inverse problem is solved through several PSO strategies. The evaluated PSOs are tested through three simulated examples corresponding to polystyrene (PS) latexes with different PSDs, and two experimental examples obtained by simply mixing 2 PS standards. In general, the evaluation results of the PSOs are excellent; and particularly, the PSO with the Trelea’s parameter set shows a better performance than other implemented PSOs.
关键词： inverse problem,particle swarm optimization algorithm,particle size distribution,Swarm Intelligence,dynamic light scattering
更新于2025-09-09 09:28:46
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Vis-NIR spectroscopy Combined with Wavelengths Selection by PSO Optimization Algorithm for Simultaneous Determination of Four Quality Parameters and Classification of Soy Sauce
摘要： The performance of Vis-NIR techniques combined with variable select by a simple modified particle swarm optimization (PSO) algorithm for the determination of four quality parameters in soy sauce was evaluated. Compared with full-spectral support vector machine regression (Full-SVMR) and SVMR based on competitive adaptive reweighted sampling (CARS-SVM) method, the application of PSO wavelength selection provided a notably improved SVM regression model. The root-mean-square error of amino acid nitrogen, salt, total acid content, and color ratio obtained by PSO-SVMR are 0.0075 g/100 ml, 0.2176 g/100 ml, 0.0077 g/100 ml, and 0.0506 in predicted sets, respectively. The correlation coefficients of predicted sets obtained by PSO-SVMR reached 0.9997, 0.9462, 0.9996, and 0.9998, respectively. Meanwhile, a classification study constructed with principal component analysis and SVM classification model based on the feature wavelengths selected by PSO shows that Vis-NIR spectra can be used to classify soy sauce according to their brands and quality. The result showed that the Vis-NIR spectroscopy technique based on PSO wavelength selection has high potential to predict the quality parameters in a nondestructive way. This analytical tool may also contribute to the detection of fraud and mislabeling in the soy sauce market and certainly contribute to improvement in quality and reliability of the soy sauce market.
关键词： Quality parameters,Wavelength selection,Modified particle swarm optimization algorithm,Visible and near-infrared spectroscopy,Soy sauce
更新于2025-09-09 09:28:46
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AIP Conference Proceedings [Author(s) SolarPACES 2017: International Conference on Concentrating Solar Power and Chemical Energy Systems - Santiago, Chile (26–29 September 2017)] - Numerical identification of mirror shapes with the backward-gazing method using an actual solar profile
摘要： Concentrated solar tower uses a huge number of heliostats and efforts are devoted to characterize the heliostats on-site at commissioning and during operation. The patented backward-gazing method with multiple cameras addresses the requirement of a fast and on-site optical characterization technique. This work concerns the study of the influence of the actual sun’s radiative intensity profile, recorded by a camera, on the accuracy of the mirror deformations identified by the post-treatment algorithms. An optimization algorithm was implemented and showed a satisfactory accuracy with maximum discrepancy of 7.3 % on the reconstructed facet slopes. The results show that the optimization method is the less sensitive to the noise and non-axisymmetricity of the sun’s intensity profile.
关键词： solar profile,backward-gazing method,heliostats,optimization algorithm,mirror deformations
更新于2025-09-04 15:30:14