A hybrid method for geological and geophysical data with multi-peak distributions using the PSO-GRG algorithm

To allow peak searching and parameter estimation for geological and geophysical data with multi-peak distributions, we explore a hybrid method based on a combination of the particle swarm optimization (PSO) and generalized reduced gradient (GRG) algorithms. After characterizing peaks using the addit...

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Vydané v:	Journal of geophysics and engineering Ročník 12; číslo 3; s. 283 - 291
Hlavní autori:	Ge, Xinmin, Fan, Yiren, Cao, Yingchang, Wang, Yang, Cong, Yunhai, Liu, Lailei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London IOP Publishing 01.06.2015 Oxford University Press
Predmet:	Algorithms backscattering electron image Convergence geological and geophysical data Geology Geophysics global convergence multi-peak distribution Nonlinearity Objective function PSO-GRG Sandstone Searching Simulated annealing Swarm intelligence geological and geophysical data multi-peak distribution backscattering electron image global convergence PSO–GRG
ISSN:	1742-2132, 1742-2140
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Abstract	To allow peak searching and parameter estimation for geological and geophysical data with multi-peak distributions, we explore a hybrid method based on a combination of the particle swarm optimization (PSO) and generalized reduced gradient (GRG) algorithms. After characterizing peaks using the additive Gaussian function, a nonlinear objective function is established, which transforms our task into a search for optimal solutions. In this process, PSO is used to obtain the initial values, aiming for global convergence, while GRG is subsequently implemented for higher stability. Iterations are stopped when the convergence criteria are satisfied. Finally, grayscale histograms of backscattering electron images of sandstone show that the proposed algorithm performs much better than other methods such as PSO, GRG, simulated annealing and differential evolution, achieving a faster convergence speed and minimal variances.
AbstractList	To allow peak searching and parameter estimation for geological and geophysical data with multi-peak distributions, we explore a hybrid method based on a combination of the particle swarm optimization (PSO) and generalized reduced gradient (GRG) algorithms. After characterizing peaks using the additive Gaussian function, a nonlinear objective function is established, which transforms our task into a search for optimal solutions. In this process, PSO is used to obtain the initial values, aiming for global convergence, while GRG is subsequently implemented for higher stability. Iterations are stopped when the convergence criteria are satisfied. Finally, grayscale histograms of backscattering electron images of sandstone show that the proposed algorithm performs much better than other methods such as PSO, GRG, simulated annealing and differential evolution, achieving a faster convergence speed and minimal variances.
Author	Wang, Yang Ge, Xinmin Cao, Yingchang Cong, Yunhai Fan, Yiren Liu, Lailei
Author_xml	– sequence: 1 givenname: Xinmin surname: Ge fullname: Ge, Xinmin email: gexinmin2002@163.com organization: CNPC Key Well Logging Laboratory in China University of Petroleum , Qingdao, 266580, Shandong, People's Republic of China – sequence: 2 givenname: Yiren surname: Fan fullname: Fan, Yiren organization: CNPC Key Well Logging Laboratory in China University of Petroleum , Qingdao, 266580, Shandong, People's Republic of China – sequence: 3 givenname: Yingchang surname: Cao fullname: Cao, Yingchang organization: China University of Petroleum School of Geosciences, Qingdao, 266580, Shandong, People's Republic of China – sequence: 4 givenname: Yang surname: Wang fullname: Wang, Yang organization: University of Houston Department of Earth and Atmospheric Sciences, Houston, TX 77054, USA – sequence: 5 givenname: Yunhai surname: Cong fullname: Cong, Yunhai organization: Geological Research Institute of Great Wall Drilling Company , CNPC, Panjin, 124010, Liaoning, People's Republic of China – sequence: 6 givenname: Lailei surname: Liu fullname: Liu, Lailei organization: China Petroleum Logging Co. Ltd , CNPC, Xi'an, 710077, Shaanxi, People's Republic of China
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Snippet	To allow peak searching and parameter estimation for geological and geophysical data with multi-peak distributions, we explore a hybrid method based on a...
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SubjectTerms	Algorithms backscattering electron image Convergence geological and geophysical data Geology Geophysics global convergence multi-peak distribution Nonlinearity Objective function PSO-GRG Sandstone Searching Simulated annealing Swarm intelligence
Title	A hybrid method for geological and geophysical data with multi-peak distributions using the PSO-GRG algorithm
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