LEADER 01369cam--2200409---450- 001 990005907620203316 005 20141114143540.0 010 $a978-88-387-8360-9 035 $a000590762 035 $aUSA01000590762 035 $a(ALEPH)000590762USA01 035 $a000590762 100 $a20131113d2013----km-y0enga50------ba 101 0 $aita 102 $aIT 105 $ay|||z|||001yy 200 1 $aCodice del lavoro$edisciplina nazionale fondamentale, disciplina fondamentale dell'Unione europea, rassegna normativa per argomento$eaggiornamenti: D.L. 31 agosto 2013, n. 101 (Razionalizzazione nelle pubbliche amministrazioni) ...$fa cura di Diego Solenne 205 $a5. ed. 210 $aSantarcangelo di Romagna$cMaggioli$d2013 215 $a1689 p.$d15 cm 225 2 $a<> Codici Tascabili$v5 410 0$12001$a<> Codici Tascabili$v, 5 454 1$12001 461 1$1001-------$12001 676 $a346.45002632 702 1$aSOLENNE,$bDiego 710 02$aITALIA$0423419 801 0$aIT$bsalbc$gISBD 912 $a990005907620203316 951 $aXXV.2.A. 207$b78383 G.$cXXV.2.A.$d00343541 959 $aBK 969 $aGIU 979 $aFIORELLA$b90$c20131113$lUSA01$h1318 979 $aFIORELLA$b90$c20131113$lUSA01$h1330 979 $aFIORELLA$b90$c20141114$lUSA01$h1435 996 $aCodice del lavoro$967273 997 $aUNISA LEADER 03922nam 22007695 450 001 9910299455103321 005 20200630053418.0 010 $a9783319092355 010 $a3319092359 024 7 $a10.1007/978-3-319-09235-5 035 $a(CKB)3710000000271819 035 $a(EBL)1966875 035 $a(SSID)ssj0001386156 035 $a(PQKBManifestationID)11830258 035 $a(PQKBTitleCode)TC0001386156 035 $a(PQKBWorkID)11351495 035 $a(PQKB)10892979 035 $a(DE-He213)978-3-319-09235-5 035 $a(MiAaPQ)EBC1966875 035 $a(PPN)183093100 035 $a(EXLCZ)993710000000271819 100 $a20141103d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aHydrological Data Driven Modelling $eA Case Study Approach /$fby Renji Remesan, Jimson Mathew 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (261 p.) 225 1 $aEarth Systems Data and Models,$x2364-5830 ;$v1 300 $aDescription based upon print version of record. 311 08$a9783319092348 311 08$a3319092340 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIntroduction -- Hydroinformatics and Data based Modelling Issues in Hydrology -- Hydroinformatics and Data based Modelling Issues in Hydrology -- Model Data Selection and Data Pre-processing Approaches -- Machine Learning and Artificial Intelligence Based Approaches -- Data based Solar Radiation Modelling -- Data based Rainfall-Runoff Modelling -- Data based Evapotranspiration Modelling -- Application of Statistical Blockade in Hydrology. 330 $aThis book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space. 410 0$aEarth Systems Data and Models,$x2364-5830 ;$v1 606 $aHydrogeology 606 $aHydrology 606 $aEngineering geology 606 $aEngineering?Geology 606 $aFoundations 606 $aHydraulics 606 $aHydrogeology$3https://scigraph.springernature.com/ontologies/product-market-codes/G19005 606 $aHydrology/Water Resources$3https://scigraph.springernature.com/ontologies/product-market-codes/211000 606 $aGeoengineering, Foundations, Hydraulics$3https://scigraph.springernature.com/ontologies/product-market-codes/T23020 615 0$aHydrogeology. 615 0$aHydrology. 615 0$aEngineering geology. 615 0$aEngineering?Geology. 615 0$aFoundations. 615 0$aHydraulics. 615 14$aHydrogeology. 615 24$aHydrology/Water Resources. 615 24$aGeoengineering, Foundations, Hydraulics. 676 $a55 676 $a551.4 676 $a551.48 676 $a624.15 700 $aRemesan$b Renji$4aut$4http://id.loc.gov/vocabulary/relators/aut$01061415 702 $aMathew$b Jimson$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299455103321 996 $aHydrological Data Driven Modelling$92518768 997 $aUNINA