LEADER 01230nam a22002773i 4500 001 991003479199707536 005 20030827082855.0 008 031111s1987 it a||||||||||||||||ita 035 $ab12432313-39ule_inst 035 $aARCHE-046560$9ExL 040 $aDip.to Lingue$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a372.6044 100 1 $aDesideri, Ippolito$0451193 245 10$aLingua italiana. Lingua straniera :$bi programmi della scuola elementare /$cIppolito Desideri, Renzo Titone 260 $aRoma :$bArmando,$c1987 300 $a234 p. :$bill. ;$c24 cm 440 2$aI problemi della didattica 650 4$aLingua italiana$xInsegnamento$xScuola elementare 700 1 $aTitone, Renzo$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0446808 907 $a.b12432313$b02-04-14$c13-11-03 912 $a991003479199707536 945 $aLE005 FONDO SEMERARO 622$g1$i2005000164989$lle005$o-$pE11.90$q-$rl$s- $t0$u0$v0$w0$x0$y.i14004008$z10-02-05 945 $aLE012 D 290$g1$i2012000072039$lle012$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i12857312$z13-11-03 996 $aLingua italiana. Lingua straniera$91459284 997 $aUNISALENTO 998 $ale005$ale012$b13-11-03$cm$da $e-$fita$git $h0$i2 LEADER 02620nam 2200397 450 001 9910583349703321 005 20230120002942.0 010 $a0-12-817027-1 035 $a(CKB)4100000007186394 035 $a(MiAaPQ)EBC5609141 035 $a(EXLCZ)994100000007186394 100 $a20181222d2019 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aData-driven solutions to transportation problems /$fedited by Yinhai Wang, Ziqiang Zeng 210 1$aAmsterdam, Netherlands :$cElsevier,$d[2019] 210 4$d©2019 215 $a1 online resource (302 pages) $cillustrations 311 $a0-12-817026-3 327 $a1. Overview of data-driven solutions -- 2. Data-driven energy efficient driving control in connected vehicle environment -- 3. Machine learning and computer vision-enabled traffic sensing data analysis and quality enhancement -- 4. Data-driven approaches for estimating travel time reliability -- 5. Urban travel behavior study based on data fusion model -- 6. Urban travel mobility exploring with large-scale trajectory data -- 7. Public transportation big data mining and analysis -- 8. Simulation-based optimization for network modeling with heterogeneous data -- 9. Network modelling and resilience analysis of air transportation : a data-driven, open-source approach -- 10. Health assessment of electric multiple units. 330 $aData-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. 606 $aTransportation$xMathematical models 615 0$aTransportation$xMathematical models. 676 $a388.015118 702 $aWang$b Yinhai 702 $aZeng$b Ziqiang$c(Assistant professor), 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910583349703321 996 $aData-driven solutions to transportation problems$92019420 997 $aUNINA