TY - JOUR ID - 1388 TI - Using a combination of genetic algorithm and particle swarm optimization algorithm for GEMTIP modeling of spectral-induced polarization data JO - Journal of Mining and Environment JA - JME LA - en SN - 2251-8592 AU - Sharifi, F. AU - Arab Amiri, A.R. AU - Kamkar Rouhani, A. AD - Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran Y1 - 2019 PY - 2019 VL - 10 IS - 2 SP - 493 EP - 505 KW - Generalized Effective-Medium Theory of Induced Polarization KW - Genetic Algorithm KW - Particle Swarm Optimization KW - Spectral-Induced Polarization DO - 10.22044/jme.2019.7902.1655 N2 - The generalized effective-medium theory of induced polarization (GEMTIP) is a newly developed relaxation model that incorporates the petro-physical and structural characteristics of polarizable rocks in the grain/porous scale to model their complex resistivity/conductivity spectra. The inversion of the GEMTIP relaxation model parameter from spectral-induced polarization data is a challenging issue because of the highly non-linear dependency of the observed data on the model parameter and non-uniqueness of the problem. To solve these problems as well as scape the local minima of the highly complicated cost function, the genetic algorithm (GA) can be applied but it has proven to be time-intensive computationally. However, this drawback can be resolved by incorporating a faster algorithm, e.g. particle swarm optimization (PSO). The aim of this work is to investigate whether recovering the model parameter of the ellipsoidal GEMTIP model from SIP data using the combined GA and PSO algorithms is possible. To achieve this aim, we set the best calculated individuals using GA as the search space of PSO, and then the best location achieved by PSO in each iteration is assigned as the updated model parameters. The results of our research work reveal that the model parameters can effectively be recovered using the approach proposed in this paper but the time constant of a noisy data that arises from the adverse dependency of this parameter on the ellipticity of a polarizable grain. Moreover, the execution time of the ellipsoidal GEMTIP modeling of complex resistivity data can be significantly improved using the proposed algorithm. UR - https://jme.shahroodut.ac.ir/article_1388.html L1 - https://jme.shahroodut.ac.ir/article_1388_050b891837f3f8d06525ee30d33ec7ba.pdf ER -