Inversion method based on stochastic optimization for particle sizing

Jaime Sanchez-Escobar Juan; Ibeth Barbosa-Santillan Liliana; Vargas-Ubera Javier; Aguilar-Valdes Felix

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Inversion method based on stochastic optimization for particle sizing

机译：基于随机优化的粒度尺寸的反演方法

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A stochastic inverse method is presented based on a hybrid evolutionary optimization algorithm (HEOA) to retrieve a monomodal particle-size distribution (PSD) from the angular distribution of scattered light. By solving an optimization problem, the HEOA (with the Fraunhofer approximation) retrieves the PSD from an intensity pattern generated by Mie theory. The analyzed light-scattering pattern can be attributed to unimodal normal, gamma, or lognormal distribution of spherical particles covering the interval of modal size parameters 46 <= alpha <= 150. The HEOA ensures convergence to the near-optimal solution during the optimization of a real-valued objective function by combining the advantages of a multimember evolution strategy and locally weighted linear regression. The numerical results show that our HEOA can be satisfactorily applied to solve the inverse light-scattering problem. (C) 2016 Optical Society of America

机译：基于混合进化优化算法（HEOA）来呈现随机逆方法，以从散射光的角度分布检索单域粒度分布（PSD）。通过解决优化问题，HEOA（带有FRAUNHOFER近似）从MIE理论产生的强度模式中检索PSD。分析的光散射图案可以归因于覆盖覆盖模态尺寸参数46 <=α<= 150的间隔的单峰正常，γ或伐木常规分布。HEOA确保在优化期间对近最佳解决方案的收敛性通过结合多方面演化策略和局部加权线性回归来实现实际价值的目标函数。数值结果表明，我们的HEOA可以令人满意地应用于解决逆散射问题。（c）2016年美国光学学会

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来源
《Applied optics》 |2016年第22期|共8页
作者
Jaime Sanchez-Escobar Juan; Ibeth Barbosa-Santillan Liliana; Vargas-Ubera Javier; Aguilar-Valdes Felix;
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Ctr Ensenanza Tecn Ind Nueva Escocia 1885 Fraccionamiento Prov 5a Secc Guadalajara 44638 Jalisco Mexico;

Univ Guadalajara CUCEA Dept Sistemas Informac Perifer Norte 799 Nucl Univ Los Belenes Zapopan 45100 Jalisco Mexico;

Univ Autonoma Ciudad Mexico Campus Cuautepec Ave Corona 320 Col Loma Palma Mexico City 54060 DF Mexico;

Inst Nacl Astrofis Opt &

Electr Luis Enrique Erro 1 Puebla 72840 Mexico;

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Inversion method based on stochastic optimization for particle sizing

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