NDLI: Regularization particle inverse algorithm of dynamic light scattering based on genetic algorithms

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2010 International Conference On Computer Design and Applications

Volume 5 - 2010

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Regularization particle inverse algorithm of dynamic light scattering based on genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Dou Zhenhai Yajing Wang Liu Wei Chen Wengang
Copyright Year	2010
Description	Author affiliation: School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, China (Dou Zhenhai; Yajing Wang; Liu Wei; Chen Wengang)
Abstract	Tikhonov regularization is an effective way in particles size inversion of dynamic light scattering (DLS). Regularization parameter choice is the key in this approach. In order to obtain the optimal regularization parameter, according to the Morozov discrepancy principle, an regularization inversion method based on genetic algorithms (GA)is proposed. It optimizes the regularization parameter within the global region by genetic algorithms, does not require a priori particle size distribution (PSD) and doesn't also define the initial value of the regularization parameter. Computer simulations datum of particles were respectively inversed by this method. The results show that when the noise level is 0∼0.001, results of unimodal distribution particles agree with the theory distribution, and double-peak feature of bimodal distribution particles is clear, maximum error of theirs inversion peak value is less than 6.67%. Therefore, regularization inversion method with GA technique has strong immunity of noises and is feasible in particles size inversion of DLS.
File Size	396366
File Format	PDF
ISBN	9781424471645
e-ISBN	9781424471645
DOI	10.1109/ICCDA.2010.5541183
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Solvents Laplace equations Particles size inversion Heuristic algorithms Light scattering Regularization parameter Optimization Genetic algorithms Particle size distribution Dynamic light scattering Integral equations Particle scattering Genetic engineering Testing
Content Type	Text
Resource Type	Article

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