LEADER 02460nam 2200577 450 001 9910788878503321 005 20170816143305.0 010 $a1-4704-0899-6 035 $a(CKB)3360000000464657 035 $a(EBL)3113779 035 $a(SSID)ssj0000889010 035 $a(PQKBManifestationID)11456900 035 $a(PQKBTitleCode)TC0000889010 035 $a(PQKBWorkID)10876418 035 $a(PQKB)11719219 035 $a(MiAaPQ)EBC3113779 035 $a(RPAM)3922211 035 $a(PPN)195413563 035 $a(EXLCZ)993360000000464657 100 $a20140902h19921992 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe inverse problem of the calculus of variations for ordinary differential equations /$fIan Anderson, Gerard Thompson 210 1$aProvidence, Rhode Island :$cAmerican Mathematical Society,$d1992. 210 4$dİ1992 215 $a1 online resource (122 p.) 225 1 $aMemoirs of the American Mathematical Society,$x0065-9266 ;$vVolume 98, Number 473 300 $a"July 1992, Volume 98, Number 473 (end of volume)." 311 $a0-8218-2533-X 320 $aIncludes bibliographical references. 327 $a""Table of Contents""; ""Abstract""; ""1. Introduction""; ""2. The Variational Bicomplex for Ordinary Differential Equations""; ""3. First Integrals and the Inverse Problem for Second Order Ordinary Differential Equations""; ""4. The Inverse Problem for Fourth Order Ordinary Differential Equations""; ""5. Exterior Differential Systems and the Inverse Problem for Second Order Ordinary Differential Equations""; ""6. Examples""; ""7. The Inverse Problem for Two Dimensional Sprays""; ""8. References"" 410 0$aMemoirs of the American Mathematical Society ;$vVolume 98, Number 473. 606 $aCalculus of variations 606 $aInverse problems (Differential equations) 606 $aPerturbation (Mathematics) 615 0$aCalculus of variations. 615 0$aInverse problems (Differential equations) 615 0$aPerturbation (Mathematics) 676 $a515/.64 700 $aAnderson$b Ian$f1952-$01486213 702 $aThompson$b Gerard$f1955- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788878503321 996 $aThe inverse problem of the calculus of variations for ordinary differential equations$93705655 997 $aUNINA LEADER 04676nam 2201489z- 450 001 9910346688303321 005 20210211 035 $a(CKB)4920000000094786 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/47751 035 $a(oapen)doab47751 035 $a(EXLCZ)994920000000094786 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aFlood Forecasting Using Machine Learning Methods 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 online resource (376 p.) 311 08$a3-03897-548-6 330 $aThis book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water 606 $aHistory of engineering and technology$2bicssc 610 $aadaptive neuro-fuzzy inference system (ANFIS) 610 $aANFIS 610 $aANN 610 $aANN-based models 610 $aartificial intelligence 610 $aartificial neural network 610 $aartificial neural networks 610 $abacktracking search optimization algorithm (BSA) 610 $abat algorithm 610 $abees algorithm 610 $abig data 610 $aclassification and regression trees (CART) 610 $aconvolutional neural networks 610 $acultural algorithm 610 $adata assimilation 610 $adata forward prediction 610 $adata scarce basins 610 $adata science 610 $adatabase 610 $adecision tree 610 $adeep learning 610 $adisasters 610 $aDongting Lake 610 $aearly flood warning systems 610 $aempirical wavelet transform 610 $aensemble empirical mode decomposition (EEMD) 610 $aensemble machine learning 610 $aensemble technique 610 $aextreme event management 610 $aextreme learning machine (ELM) 610 $aflash-flood 610 $aflood events 610 $aflood forecast 610 $aflood forecasting 610 $aflood inundation map 610 $aflood prediction 610 $aflood routing 610 $aflood susceptibility modeling 610 $aforecasting 610 $aGoogle Maps 610 $aHaraz watershed 610 $ahigh-resolution remote-sensing images 610 $ahybrid & 610 $ahybrid neural network 610 $ahydrograph predictions 610 $ahydroinformatics 610 $ahydrologic model 610 $ahydrologic models 610 $ahydrometeorology 610 $aimproved bat algorithm 610 $ainvasive weed optimization 610 $aKarahan flood 610 $alag analysis 610 $aLower Yellow River 610 $aLSTM 610 $aLSTM network 610 $amachine learning 610 $amachine learning methods 610 $amethod of tracking energy differences (MTED) 610 $amicro-model 610 $amonthly streamflow forecasting 610 $aMuskingum model 610 $anatural hazards & 610 $anonlinear Muskingum model 610 $aoptimization 610 $aparameters 610 $aparticle filter algorithm 610 $aparticle swarm optimization 610 $aphase space reconstruction 610 $apostprocessing 610 $aprecipitation-runoff 610 $arainfall-runoff 610 $arainfall-runoff 610 $arandom forest 610 $arating curve method 610 $areal-time 610 $arecurrent nonlinear autoregressive with exogenous inputs (RNARX) 610 $arunoff series 610 $aself-organizing map 610 $aself-organizing map (SOM) 610 $asensitivity 610 $asoft computing 610 $aSt. Venant equations 610 $astopping criteria 610 $astreamflow predictions 610 $asuperpixel 610 $asupport vector machine 610 $asurvey 610 $athe Three Gorges Dam 610 $athe upper Yangtze River 610 $atime series prediction 610 $auncertainty 610 $aurban water bodies 610 $awater level forecast 610 $aWilson flood 610 $awolf pack algorithm 615 7$aHistory of engineering and technology 700 $aChang$b Fi-John$4auth$01287662 702 $aHsu$b Kuolin$4auth 702 $aChang$b Li-Chiu$4auth 906 $aBOOK 912 $a9910346688303321 996 $aFlood Forecasting Using Machine Learning Methods$93020270 997 $aUNINA