LEADER 00928nam0 22002531i 450 001 UON00123423 005 20231205102726.678 100 $a20020107d1976 |0itac50 ba 101 $afre 102 $aKR 105 $a|||| 1|||| 200 1 $aCoree telle qu'elle est 210 $aSeoul$cService d'Information pur l'Etranger$d1976 215 $a156 p.$cill., c. di tav.$d18 cm 606 $aCOREA$xGUIDE$3UONC001238$2FI 620 $aKR$dSeoul$3UONL000020 686 $aCOR I$cCOREA - GENERALIA$2A 712 $aService d'Information pour l'Etranger$3UONV262125$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00123423 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI COR I 012 $eSI SA 5240 5 012 996 $aCoree telle qu'elle est$91317793 997 $aUNIOR LEADER 02126nam 2200361za 450 001 9910830444603321 005 20230721005755.0 010 $a9780470611463 (e-book) 010 $a9781848210608 (hbk.) 035 $a(MiAaPQ)EBC477673 035 $a(EXLCZ)992550000000005885 100 $a20080408d2008 uy 0 101 0 $aeng 135 $aur|n|nnn||||| 200 00$aAdvanced mapping of environmental data$b[electronic resource] $egeostatistics, machine learning, and Bayesian maximum entropy /$fedited by Mikhail Kanevski 210 $aLondon $cISTE ;$aHoboken, N.J. $cWiley$d2008 215 $a1 online resource (xiii, 313 p.) $cill 225 1 $aISTE ;$vv.62 320 $aIncludes bibliographical references and index. 327 $aChapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy ? BME -- Index. 330 $aThis book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more. 410 0$aISTE. 606 $aGeology$xStatistical methods 606 $aMachine learning 606 $aBayesian statistical decision theory 615 0$aGeology$xStatistical methods. 615 0$aMachine learning. 615 0$aBayesian statistical decision theory. 676 $a550.1519542 701 $aKanevski$b Mikhail$01701177 912 $a9910830444603321 996 $aAdvanced mapping of environmental data$94084742 997 $aUNINA