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Genetic programming model for estimating soil suction in shallow soil layers in the vicinity of a tree
Zhi-Liang Cheng1; Wan-Huan Zhou1; Ankit Garg2
2020-01-24
Source PublicationEngineering Geology
ISSN0013-7952
Volume268Pages:105506
Abstract

Soil suction, an important parameter in the safety and risk assessment of geotechnical and green infrastructures, is greatly affected by plants and weather in the shallow soil layers of urban landscapes/green infrastructure. In this study, a computational model consisting of a drying-cycle model and wetting-cycle model was developed by means of a genetic programming method to depict variations in soil suction using select influential parameters. The input data in the model development were measured in a field monitoring test on the campus of the University of Macau. Soil suction was quantified by field monitoring at different distances (0.5 m, 1.5 m, and 3.0 m) from a tree, at a constant depth of 20 cm, with selected influential parameters including initial soil suction, air humidity, rainfall amount, cycle duration, and ratio of distance from tree to tree canopy. Based on the performance analysis, the efficiency and reliability of the proposed computational model are validated. The importance of each input and the coupled effect of each two input variables on the output were investigated using global sensitivity analysis. It can be concluded that the proposed computational model based on the artificial intelligence simulation method describes the relationship between field soil suction in drying–wetting cycles and select input variables within an acceptable degree of error. Accordingly, it can serve as a tool for supporting geotechnical construction design and for assessing the safety and risk of geotechnical green infrastructures.

KeywordDrying Cycle Genetic Programming Global Sensitivity Analysis Performance Analysis Soil Suction Wetting Cycle
DOI10.1016/j.enggeo.2020.105506
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Geology
WOS SubjectEngineering, Geological ; Geosciences, Multidisciplinary
WOS IDWOS:000525398800007
PublisherELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
Scopus ID2-s2.0-85079188189
Fulltext Access
FWCI4.2282214
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Corresponding AuthorWan-Huan Zhou
Affiliation1.State Key Laboratory of Internet of Things for Smart City, Department of Civil and Environmental Engineering, University of Macau, Macau SAR, China
2.Department of Civil and Environmental Engineering, Guangdong Engineering Center for Structure Safety and Health Monitoring, Shantou University, Shantou, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhi-Liang Cheng,Wan-Huan Zhou,Ankit Garg. Genetic programming model for estimating soil suction in shallow soil layers in the vicinity of a tree[J]. Engineering Geology,2020,268:105506.
APA Zhi-Liang Cheng,Wan-Huan Zhou,&Ankit Garg.(2020).Genetic programming model for estimating soil suction in shallow soil layers in the vicinity of a tree.Engineering Geology,268,105506.
MLA Zhi-Liang Cheng,et al."Genetic programming model for estimating soil suction in shallow soil layers in the vicinity of a tree".Engineering Geology 268(2020):105506.
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