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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/npg-2019-36
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-2019-36
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 02 Jul 2019

Submitted as: research article | 02 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Nonlinear Processes in Geophysics (NPG).

BP Neural Network and improved Particle Swarm Optimization for Transient Electromagnetic Inversion

Huaiqing Zhang, Ruiyou Li, Nian Yu, Ruiheng Li, and Qiong Zhuang Huaiqing Zhang et al.
  • The State Key Laboratory of Transmission Equipment and System Safety and Electrical New Technology, Chongqing University, Chongqing, 400044, China

Abstract. As one of the most active nonlinear inversion methods in transient electromagnetic (TEM) inversion, the back propagation (BP) neural network has high efficiency because the complicated forward model calculation is unnecessary in iteration. The global optimization ability of the particle swarm optimization (PSO) is adopted for amending BP's sensitivity on initial parameters, which avoids it falling into local optimum. A chaotic oscillation inertia weight PSO (COPSO) is proposed in accelerating convergence. The COPSO-BP algorithm performance is validated by two typical testing functions and then by two geoelectric models inversion. The results show that the COPSO-BP method has better accuracy, stability and relative less training times. The proposed algorithm has a higher fitting degree for the data inversion, and it is feasible in geophysical inverse applications.

Huaiqing Zhang et al.
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Status: open (extended)
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Latest update: 15 Sep 2019
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Short summary
The COPSO-BP algorithm is proposed for transient electromagnetic inversion. The BP's initial weight and threshold parameters were trained by COPSO algorithm, which overcomes the shortcoming of single BP falls easily into local optimum. The layered geoelectric model inversion showed that COPSO-BP method has better accuracy, stability and relative less training times. It is expected to be used in 1-D direct current sounding, 1-D magnetotelluric sounding, seismic wave impedance, source detection.
The COPSO-BP algorithm is proposed for transient electromagnetic inversion. The BP's initial...
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