Articles | Volume 26, issue 4
https://doi.org/10.5194/npg-26-445-2019
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
26 Nov 2019
Research article |
| 26 Nov 2019
| 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
Related subject area
Subject: Time series, machine learning, networks, stochastic processes, extreme events | Topic: Solid earth, continental surface, biogeochemistry | Techniques: Big data and artificial intelligence
Stability and uncertainty assessment of geoelectrical resistivity model parameters: a new hybrid metaheuristic algorithm and posterior probability density function approach
Nonlin. Processes Geophys., 31, 7–24, 2024
Cited articles
Dai, Q., Jiang, F., and Dong, L.: Nonlinear inversion for electrical
resistivity tomography based on chaotic DE-BP algorithm, J. Cent. South.
Univ., 21, 2018–2025, https://doi.org/10.1007/s11771-014-2151-9, 2014.
Fernández Martínez, J. L., García Gonzalo, E., Fernández
Álvarez, J. P., Kuzma, H. A., and Menéndez Pérez, C. O.: PSO: A
powerful algorithm to solve geophysical inverse problems: Application to a
1D-DC resistivity case, J. Appl. Geophys., 71, 13–25,
https://doi.org/10.1016/j.jappgeo.2010.02.001, 2010.
Godio, A. and Santilano, A.: On the optimization of electromagnetic
geophysical data: Application of the PSO algorithm, J. Appl.
Geophys., 148, 163–174, https://doi.org/10.1016/j.jappgeo.2017.11.016,
2018.
Jha, M. K., Kumar, S., and Chowdhury, A.: Vertical electrical sounding
survey and resistivity inversion using genetic algorithm optimization
technique, J. Hydrol., 359, 71–87,
https://doi.org/10.1016/j.jhydrol.2008.06.018, 2008.
Jiang, F., Dai, Q., and Dong, L.: An ICPSO-RBFNN nonlinear inversion for
electrical resistivity imaging, J. Cent. South. Univ., 23, 2129–2138,
https://doi.org/10.1007/s11771-016-3269-8, 2016a.
