000 03964nam a22006015i 4500
001 978-3-319-75608-0
003 DE-He213
005 20210201191448.0
007 cr nn 008mamaa
008 180321s2018 gw | s |||| 0|eng d
020 _a9783319756080
_9978-3-319-75608-0
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM075000
_2bisacsh
072 7 _aUKN
_2thema
082 0 4 _a004.6
_223
245 1 0 _aTraffic Mining Applied to Police Activities
_h[electronic resource] :
_bProceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /
_cedited by Fabio Leuzzi, Stefano Ferilli.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXII, 155 p. 39 illus., 33 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v728
500 _aAcceso multiusuario
520 _aThis book presents high-quality original contributions on the development of automatic traffic analysis systems that are able to not only anticipate traffic scenarios, but also understand the behavior of road users (vehicles, bikes, trucks, etc.) in order to provide better traffic management, prevent accidents and, potentially, identify criminal behaviors. Topics also include traffic surveillance and vehicle accident analysis using formal concept analysis, convolutional and recurrent neural networks, unsupervised learning and process mining. The content is based on papers presented at the 1st Italian Conference for the Traffic Police (TRAP), which was held in Rome in October 2017. This conference represents a targeted response to the challenges facing the police in connection with managing massive traffic data, finding patterns from historical datasets, and analyzing complex traffic phenomena in order to anticipate potential criminal behaviors. The book will appeal to researchers, practitioners and decision makers interested in traffic monitoring and analysis, traffic modeling and simulation, mobility and social data mining, as well as members of the police.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aComputer communication systems.
650 0 _aTransportation engineering.
650 0 _aTraffic engineering.
650 0 _aData mining.
650 0 _aOperations research.
650 0 _aManagement science.
650 1 4 _aComputer Communication Networks.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I13022
650 2 4 _aTransportation Technology and Traffic Engineering.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T23120
650 2 4 _aData Mining and Knowledge Discovery.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I18030
650 2 4 _aOperations Research, Management Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M26024
700 1 _aLeuzzi, Fabio.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFerilli, Stefano.
_eeditor.
_0(orcid)0000-0003-1118-0601
_1https://orcid.org/0000-0003-1118-0601
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319756073
776 0 8 _iPrinted edition:
_z9783319756097
830 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v728
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-75608-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c243758
_d243757