Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting
A project that needs to be uplifted by high-pressure jet grouting (HPJG) is exposed to particular geological and engineering circumstances; meanwhile, HPJG has intense subjectivity, short of the theoretical base, to ascertain the influence angle β and enlarged radius Δa, which are the main parameter...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8833784 |
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| author | Wukui Dai Li Liang Bingji Zhang |
| author_facet | Wukui Dai Li Liang Bingji Zhang |
| author_sort | Wukui Dai |
| collection | DOAJ |
| description | A project that needs to be uplifted by high-pressure jet grouting (HPJG) is exposed to particular geological and engineering circumstances; meanwhile, HPJG has intense subjectivity, short of the theoretical base, to ascertain the influence angle β and enlarged radius Δa, which are the main parameters that affect the uplift effect. Therefore, we proposed a new method based on the firefly optimization algorithm to search for the optimal solution for the target function. Stochastic medium theory (SMT) was used in this article, in which the effect of single-pile HPJG was simulated as the superposition effect of the foam slurry at the same distance, to construct a stochastic medium prediction model of the effect of uplift due to multi-HPJG. In accordance with the range of the prediction results of single-pile HPJG and combined with in situ monitoring data to define the target function, the optimal parameters are substituted into the prediction model to predict the subsequent uplift effect due to HPJG. As a result of the global optimization capacity and by comparison with the genetic algorithm, the FOA has a greater advantage in terms of effectiveness and precision. Finally, it is proven that the prediction result meets the requirement of the prediction in advance by statistical data. |
| format | Article |
| id | doaj-art-f423e389e7ab4959b6bb6590e0604588 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-f423e389e7ab4959b6bb6590e06045882025-02-03T06:47:00ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88337848833784Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet GroutingWukui Dai0Li Liang1Bingji Zhang2School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaSchool of Resources & Civil Engineering, Northeastern University, Shenyang 110819, ChinaChina Northeast Architectural Design & Research Institute Co. Ltd, Shenyang 110006, ChinaA project that needs to be uplifted by high-pressure jet grouting (HPJG) is exposed to particular geological and engineering circumstances; meanwhile, HPJG has intense subjectivity, short of the theoretical base, to ascertain the influence angle β and enlarged radius Δa, which are the main parameters that affect the uplift effect. Therefore, we proposed a new method based on the firefly optimization algorithm to search for the optimal solution for the target function. Stochastic medium theory (SMT) was used in this article, in which the effect of single-pile HPJG was simulated as the superposition effect of the foam slurry at the same distance, to construct a stochastic medium prediction model of the effect of uplift due to multi-HPJG. In accordance with the range of the prediction results of single-pile HPJG and combined with in situ monitoring data to define the target function, the optimal parameters are substituted into the prediction model to predict the subsequent uplift effect due to HPJG. As a result of the global optimization capacity and by comparison with the genetic algorithm, the FOA has a greater advantage in terms of effectiveness and precision. Finally, it is proven that the prediction result meets the requirement of the prediction in advance by statistical data.http://dx.doi.org/10.1155/2020/8833784 |
| spellingShingle | Wukui Dai Li Liang Bingji Zhang Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting Advances in Civil Engineering |
| title | Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting |
| title_full | Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting |
| title_fullStr | Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting |
| title_full_unstemmed | Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting |
| title_short | Firefly Optimization Algorithm for the Prediction of Uplift due to High-Pressure Jet Grouting |
| title_sort | firefly optimization algorithm for the prediction of uplift due to high pressure jet grouting |
| url | http://dx.doi.org/10.1155/2020/8833784 |
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