An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion
In order to improve the inversion accuracy of electrical resistivity tomography (ERT) and overcome the limitations of traditional linear methods, this paper proposes an improved shuffled frog leaping algorithm (SFLA). First, an equilibrium grouping strategy is designed to balance the contribution we...
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2025-07-01
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| author | Fuyu Jiang Likun Gao Run Han Minghui Dai Haijun Chen Jiong Ni Yao Lei Xiaoyu Xu Sheng Zhang |
| author_facet | Fuyu Jiang Likun Gao Run Han Minghui Dai Haijun Chen Jiong Ni Yao Lei Xiaoyu Xu Sheng Zhang |
| author_sort | Fuyu Jiang |
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| description | In order to improve the inversion accuracy of electrical resistivity tomography (ERT) and overcome the limitations of traditional linear methods, this paper proposes an improved shuffled frog leaping algorithm (SFLA). First, an equilibrium grouping strategy is designed to balance the contribution weight of each subgroup to the global optimal solution, suppressing the local optimum traps caused by the dominance of high-quality groups. Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. Additionally, the root mean square error is reduced by 57%. In the engineering validation at the Baota Mountain mining area in Jurong, the improved SFLA inversion clearly reveals the undulating bedrock morphology. At a measuring point 55 m along the profile, the bedrock depth is 14.05 m (ZK3 verification value 12.0 m, error 17%), and at 96 m, the depth is 6.9 m (ZK2 verification value 6.7 m, error 3.0%). The characteristic of deeper bedrock to the south and shallower to the north is highly consistent with the terrain and drilling data (RMSE = 1.053). This algorithm provides reliable technical support for precise detection of complex geological structures using ERT. |
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| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-07-01 |
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| spelling | doaj-art-0e2e231e510c4d0c8da5d79597092bb02025-08-20T04:00:49ZengMDPI AGApplied Sciences2076-34172025-07-011515852710.3390/app15158527An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography InversionFuyu Jiang0Likun Gao1Run Han2Minghui Dai3Haijun Chen4Jiong Ni5Yao Lei6Xiaoyu Xu7Sheng Zhang8School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaThe First Geological Brigade of Jiangsu Geological Bureau, Nanjing 210041, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaNanjing Hydraulic Research Hydraulic Research Institute, Nanjing 210029, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 210098, ChinaIn order to improve the inversion accuracy of electrical resistivity tomography (ERT) and overcome the limitations of traditional linear methods, this paper proposes an improved shuffled frog leaping algorithm (SFLA). First, an equilibrium grouping strategy is designed to balance the contribution weight of each subgroup to the global optimal solution, suppressing the local optimum traps caused by the dominance of high-quality groups. Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. Additionally, the root mean square error is reduced by 57%. In the engineering validation at the Baota Mountain mining area in Jurong, the improved SFLA inversion clearly reveals the undulating bedrock morphology. At a measuring point 55 m along the profile, the bedrock depth is 14.05 m (ZK3 verification value 12.0 m, error 17%), and at 96 m, the depth is 6.9 m (ZK2 verification value 6.7 m, error 3.0%). The characteristic of deeper bedrock to the south and shallower to the north is highly consistent with the terrain and drilling data (RMSE = 1.053). This algorithm provides reliable technical support for precise detection of complex geological structures using ERT.https://www.mdpi.com/2076-3417/15/15/8527electrical resistivity tomographyShuffled Frog Leaping Algorithmbalanced groupingadaptive moving step sizeBaota Mountain mining area |
| spellingShingle | Fuyu Jiang Likun Gao Run Han Minghui Dai Haijun Chen Jiong Ni Yao Lei Xiaoyu Xu Sheng Zhang An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion Applied Sciences electrical resistivity tomography Shuffled Frog Leaping Algorithm balanced grouping adaptive moving step size Baota Mountain mining area |
| title | An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion |
| title_full | An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion |
| title_fullStr | An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion |
| title_full_unstemmed | An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion |
| title_short | An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion |
| title_sort | improved shuffled frog leaping algorithm for electrical resistivity tomography inversion |
| topic | electrical resistivity tomography Shuffled Frog Leaping Algorithm balanced grouping adaptive moving step size Baota Mountain mining area |
| url | https://www.mdpi.com/2076-3417/15/15/8527 |
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