Articles | Volume 26, issue 4
https://doi.org/10.5194/npg-26-445-2019
https://doi.org/10.5194/npg-26-445-2019
Research article
 | 
26 Nov 2019
Research article |  | 26 Nov 2019

A fast approximation for 1-D inversion of transient electromagnetic data by using a back propagation neural network and improved particle swarm optimization

Ruiyou Li, Huaiqing Zhang, Nian Yu, Ruiheng Li, and Qiong Zhuang

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Latest update: 23 Nov 2024
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Short summary
The chaotic-oscillation inertia weight back propagation (COPSO-BP) algorithm is proposed for transient electromagnetic inversion. The BP's initial weight and threshold parameters were trained by COPSO, overcoming the BP falling into a local optimum. Inversion of the layered geoelectric model showed that the COPSO-BP method is accurate and stable and needs less training time. It can be used in 1-D direct current sounding, 1-D magnetotelluric sounding, seismic-wave impedance and source detection.