LEADER 01064nam a2200241 i 4500 001 991001921799707536 008 121213s1972 it 000 0 ita d 035 $ab1409230x-39ule_inst 040 $aBiblioteca Interfacoltà$bita 082 04$a937 100 1 $aVacca, Nicola $0450456 245 10$aBreve nota sulle origini e sulla lingua dei Messapi /$cNicola Vacca 260 $aBari :$bTip. del Sud,$c[1972?] 300 $aP. 193-195 ;$c25 cm 500 $aEstratto da: Archivio Storico Pugliese, a. 25 (1972), fasc. 1-2 650 4$aMessapi$xStoria$xOrigini$ySec. 3. a. C. 907 $a.b1409230x$b02-04-14$c13-12-12 912 $a991001921799707536 945 $aLE002 Fondo Vacca Estr. 030$g1$i2002000897015$lle002$op$pE15.00$q-$rn$so $t0$u0$v0$w0$x0$y.i15469694$z13-12-12 945 $aLE002 Fondo Vacca Estr. 031$g2$i2002000897022$lle002$op$pE15.00$q-$rn$so $t0$u0$v0$w0$x0$y.i15469700$z13-12-12 996 $aBreve nota sulle origini e sulla lingua dei Messapi$9241432 997 $aUNISALENTO 998 $ale002$b13-12-12$cm$da $e-$fita$git $h0$i0 LEADER 02362nam 2200409za 450 001 9910220021003321 005 20230809225552.0 010 $a9783038423270 (ebook) 010 $a9783038423263 (pbk.) 024 8 $a10.3390/books978-3-03842-327-0 035 $a(CKB)3800000000216507 035 $a(ScCtBLL)577388c0-ca0e-4eb7-b505-42a0eea37a19 035 $a(OCoLC)1162799915 035 $a(EXLCZ)993800000000216507 100 $a20191103d2017 uy 0 101 0 $aeng 135 $auru|||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aUse of meta-heuristic techniques in rainfall-runoff modelling /$fspecial issue editor Kwok-wing Chau 210 $aBasel $cMDPI AG$d2017 215 $a1 online resource (vii, 246 p.) $cill 300 $aSpecial issue published in Water. 330 $aEach year, extreme floods, which appear to be occurring more frequently in recent years (owing to climate change), lead to enormous economic damage and human suffering around the world. It is therefore imperative to be able to accurately predict both the occurrence time and magnitude of peak discharge in advance of an impending flood event. The use of meta-heuristic techniques in rainfall-runoff modeling is a growing field of endeavor in water resources management. These techniques can be used to calibrate data-driven rainfall-runoff models to improve forecasting accuracies. This book, being also a Special Issue of the journal Water, is designed to fill the analytical void by including fourteen articles concerning advances in the contemporary use of meta-heuristic techniques in rainfall-runoff modeling. The information and analyses are intended to contribute to the development and implementation of effective hydrological predictions, and thus, of appropriate precautionary measures. 606 $aRain and rainfall$xMathematical models 606 $aRunoff$xMathematical models 615 0$aRain and rainfall$xMathematical models. 615 0$aRunoff$xMathematical models. 676 $a551.488 701 $aChau$b Kwok Wing$0874291 712 02$aMultidisciplinary Digital Publishing Institute. 801 0$bScCtBLL 801 1$bScCtBLL 912 $a9910220021003321 996 $aUse of meta-heuristic techniques in rainfall-runoff modelling$91952092 997 $aUNINA LEADER 03871nam 2200913z- 450 001 9910557610303321 005 20220321 035 $a(CKB)5400000000045299 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/79633 035 $a(oapen)doab79633 035 $a(EXLCZ)995400000000045299 100 $a20202203d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aComputational Optimizations for Machine Learning 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (276 p.) 311 08$a3-0365-3186-6 311 08$a3-0365-3187-4 330 $aThe present book contains the 10 articles finally accepted for publication in the Special Issue "Computational Optimizations for Machine Learning" of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity. 606 $aMathematics & science$2bicssc 606 $aResearch & information: general$2bicssc 610 $aARIMA model 610 $aartificial intelligence 610 $aautoencoders 610 $abed roughness 610 $abio-inspired algorithms 610 $aCNN architecture 610 $acomputational intelligence 610 $aconvolutional neural network 610 $adeep compression 610 $adeep learning 610 $adeep neural networks 610 $aDNN 610 $aenergy dissipation 610 $aevolution of weights 610 $aevolutionary algorithms 610 $aevolutionary computation 610 $afeature selection 610 $afloating-point numbers 610 $aFLOW-3D 610 $ageneralization error 610 $agenetic algorithms 610 $ahardware acceleration 610 $aHeating, Ventilation and Air Conditioning (HVAC) 610 $ahydraulic jumps 610 $alow power 610 $amachine learning 610 $ameta-heuristic optimization 610 $ametaheuristics search 610 $amodel predictive control 610 $amulti-objective optimization 610 $anature inspired algorithms 610 $aneural networks 610 $anonlinear systems 610 $aonline model selection 610 $aonline optimization 610 $aprecipitation nowcasting 610 $aquantization 610 $aradar data 610 $arecurrent neural networks 610 $aReLU 610 $asensitivity analysis 610 $asmart building 610 $asoft computing 610 $aswarm intelligence 610 $atime series analysis 610 $atraining 615 7$aMathematics & science 615 7$aResearch & information: general 700 $aGabbay$b Freddy$4edt$01304465 702 $aGabbay$b Freddy$4oth 906 $aBOOK 912 $a9910557610303321 996 $aComputational Optimizations for Machine Learning$93027447 997 $aUNINA LEADER 04879oam 22011654 450 001 9910959813103321 005 20251116183853.0 010 $a9786613820808 010 $a9781462307432 010 $a1462307434 010 $a9781452723914 010 $a1452723915 010 $a9781282413764 010 $a1282413767 010 $a9781451908954 010 $a1451908954 035 $a(CKB)3360000000443119 035 $a(EBL)3014464 035 $a(SSID)ssj0000943267 035 $a(PQKBManifestationID)11580583 035 $a(PQKBTitleCode)TC0000943267 035 $a(PQKBWorkID)10975527 035 $a(PQKB)10152507 035 $a(OCoLC)694141132 035 $a(IMF)WPIEE2006101 035 $a(NBER)w12235 035 $a(MiAaPQ)EBC3014464 035 $a(IMF)WPIEA2006101 035 $aWPIEA2006101 035 $a(EXLCZ)993360000000443119 100 $a20020129d2006 uf 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSudden Stops and IMF-Supported Programs /$fBarry Eichengreen, Poonam Gupta, Ashoka Mody 205 $a1st ed. 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2006. 215 $a1 online resource (53 p.) 225 1 $aIMF Working Papers 300 $a"May 2006". 311 08$a9781451863611 311 08$a1451863616 320 $aIncludes bibliographical references. 327 $a""Contents""; ""I. INTRODUCTION""; ""II. SUDDEN STOPS AND MULTILATERAL INSURANCE""; ""III. CAPITAL FLOWS AND SUDDEN STOPS""; ""IV. IMF-SUPPORTED PROGRAMS""; ""V. MULTIVARIATE ANALYSIS""; ""VI. IMF-SUPPORTED PROGRAMS AND SUDDEN STOPS""; ""VII. EXTENSIONS""; ""VIII. CONCLUSIONS AND IMPLICATIONS""; ""Appendix Table A1. Countries in the Sample and Sudden Stop Dates Country Year""; ""Appendix Table A2. Determinants of Sudden Stops: Sensitivity to Sample Composition""; ""Appendix II: Sources of Data and Construction of Variables""; ""REFERENCES"" 330 3 $aCould a high-access, quick-disbursing "insurance facility" in the IMF help to reduce the incidence of sharp interruptions in capital flows ("sudden stops")? We contribute to the debate around this question by analyzing the impact of conventional IMF-supported programs on the incidence of sudden stops. Correcting for the non-random assignment of programs, we find that sudden stops are fewer and generally less severe when an IMF arrangement exists and that this form of "insurance" works best for countries with strong fundamentals. In contrast there is no evidence that a Fund-supported program attenuates the output effects of capital account reversals if these nonetheless occur. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2006/101 606 $aCapital movements$xEconometric models 606 $aBalance of payments$2imf 606 $aCapital flows$2imf 606 $aCapital movements$2imf 606 $aCredit$2imf 606 $aCurrency$2imf 606 $aCurrent Account Adjustment$2imf 606 $aCurrent account$2imf 606 $aDomestic credit$2imf 606 $aExchange rate arrangements$2imf 606 $aExports and Imports$2imf 606 $aForeign Exchange$2imf 606 $aForeign exchange$2imf 606 $aInternational economics$2imf 606 $aInternational Investment$2imf 606 $aLong-term Capital Movements$2imf 606 $aMonetary economics$2imf 606 $aMonetary Policy, Central Banking, and the Supply of Money and Credit: General$2imf 606 $aMoney and Monetary Policy$2imf 606 $aShort-term Capital Movements$2imf 606 $aSudden stops$2imf 607 $aUnited States$2imf 615 0$aCapital movements$xEconometric models. 615 7$aBalance of payments 615 7$aCapital flows 615 7$aCapital movements 615 7$aCredit 615 7$aCurrency 615 7$aCurrent Account Adjustment 615 7$aCurrent account 615 7$aDomestic credit 615 7$aExchange rate arrangements 615 7$aExports and Imports 615 7$aForeign Exchange 615 7$aForeign exchange 615 7$aInternational economics 615 7$aInternational Investment 615 7$aLong-term Capital Movements 615 7$aMonetary economics 615 7$aMonetary Policy, Central Banking, and the Supply of Money and Credit: General 615 7$aMoney and Monetary Policy 615 7$aShort-term Capital Movements 615 7$aSudden stops 700 $aEichengreen$b Barry$0318418 701 $aGupta$b Poonam$01816118 701 $aMody$b Ashoka$0888386 712 02$aInternational Monetary Fund.$bEuropean Department. 801 0$bDcWaIMF 906 $aBOOK 912 $a9910959813103321 996 $aSudden Stops and IMF-Supported Programs$94371795 997 $aUNINA