LEADER 03580nam  22006495  450 
001 9910366611103321
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010   $a981-13-7422-8
024 7 $a10.1007/978-981-13-7422-7
035   $a(CKB)4100000008525932
035   $a(DE-He213)978-981-13-7422-7
035   $a(MiAaPQ)EBC5771085
035   $a(PPN)235667234
035   $a(EXLCZ)994100000008525932
100   $a20190430d2020      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMARS Applications in Geotechnical Engineering Systems$b[electronic resource] $eMulti-Dimension with Big Data /$fby Wengang Zhang
205   $a1st ed. 2020.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020.
215   $a1 online resource (XXI, 240 p. 99 illus., 64 illus. in color.) 
311   $a981-13-7421-X 
327   $aIntroduction -- MARS methodology -- Simple MARS modeling examples -- MARS use in prediction of collapse potential for compacted soils -- MARS use in prediction of diaphragm wall deflections in soft clays -- MARS use in HP-pile drivability assessment -- MARS use in assessment of soil liquefaction -- MARS use in evaluating entry-type excavation stability -- Summary and conclusions.
330   $aThis book presents the application of a comparatively simple nonparametric regression algorithm, known as the multivariate adaptive regression splines (MARS) surrogate model, which can be used to approximate the relationship between the inputs and outputs, and express that relationship mathematically. The book first describes the MARS algorithm, then highlights a number of geotechnical applications with multivariate big data sets to explore the approach?s generalization capabilities and accuracy. As such, it offers a valuable resource for all geotechnical researchers, engineers, and general readers interested in big data analysis. .
606   $aEngineering geology
606   $aEngineering?Geology
606   $aFoundations
606   $aHydraulics
606   $aGeotechnical engineering
606   $aBig data
606   $aInput-output equipment (Computers)
606   $aGeoengineering, Foundations, Hydraulics$3https://scigraph.springernature.com/ontologies/product-market-codes/T23020
606   $aGeotechnical Engineering & Applied Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G37010
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
606   $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070
606   $aInput/Output and Data Communications$3https://scigraph.springernature.com/ontologies/product-market-codes/I12042
615  0$aEngineering geology.
615  0$aEngineering?Geology.
615  0$aFoundations.
615  0$aHydraulics.
615  0$aGeotechnical engineering.
615  0$aBig data.
615  0$aInput-output equipment (Computers).
615 14$aGeoengineering, Foundations, Hydraulics.
615 24$aGeotechnical Engineering & Applied Earth Sciences.
615 24$aBig Data.
615 24$aBig Data/Analytics.
615 24$aInput/Output and Data Communications.
676   $a624.15
700   $aZhang$b Wengang$4aut$4http://id.loc.gov/vocabulary/relators/aut$0973112
906   $aBOOK
912   $a9910366611103321
996   $aMARS Applications in Geotechnical Engineering Systems$92214001
997   $aUNINA