Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration
Author(s): |
Xue Liu
Chunwei Pan Fangkun Zheng Ying Sun Qingsong Gou |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2022, v. 2022 |
Page(s): | 1-9 |
DOI: | 10.1155/2022/1555877 |
Abstract: |
Before the construction of the bridge bored pile in the karst area, geological conditions of the excavation area should be investigated. In order to avoid the karst caves in underground space making adverse impacts on the construction, bearing capacity, and stability of pile foundation, in this paper, we use the transient electromagnetic method to detect the karst development in the bearing layer of the pile foundation, which is different from the traditional karst survey method. To improve the interpretation accuracy of transient electromagnetic detection for karst caves, the quantum particle swarm optimization (QPSO) algorithm was combined with the smooth constrained least squares (CLS) algorithm, and the transient electromagnetic inversion based on the QPSO-CLS joint algorithm was generated. Better inversion results were achieved by the proposed method in this study. Based on the inversion calculation results of simulation data and field test data, it is further demonstrated that the QPSO-CLS joint algorithm has high optimization efficiency without manually setting the initial model. The interpretation results are consistent with the theoretical model and drilling logging results, which proves the adaptability of the proposed algorithm. |
Copyright: | © Xue Liu et al. et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10691815 - Published on:
23/09/2022 - Last updated on:
10/11/2022