Eintrag weiter verarbeiten

A generative deep learning approach towards decisions in transient gas networks

Gespeichert in:

Personen und Körperschaften: Anderson, Lovis (VerfasserIn), Turner, Mark (VerfasserIn), Koch, Thorsten (VerfasserIn), Zuse Institute Berlin (Herausgebendes Organ)
Titel: A generative deep learning approach towards decisions in transient gas networks/ Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch
Format: E-Book
Sprache: Englisch
veröffentlicht:
Berlin Zuse Institute Berlin January 4, 2021
Gesamtaufnahme: Konrad-Zuse-Zentrum für Informationstechnik Berlin: ZIB-Report ; 2020, [38]
Schlagwörter:
Quelle: Verbunddaten SWB
Lizenzfreie Online-Ressourcen
LEADER 02194cam a2200517 4500
001 0-1745974350
003 DE-627
005 20220224194639.0
007 cr uuu---uuuuu
008 210128s2021 gw |||||ot 00| ||eng c
035 |a (DE-627)1745974350 
035 |a (DE-599)KXP1745974350 
035 |a (OCoLC)1299238071 
040 |a DE-627  |b ger  |c DE-627  |e rda 
041 |a eng 
044 |c XA-DE-BE 
100 1 |a Anderson, Lovis  |e VerfasserIn  |4 aut 
245 1 2 |a A generative deep learning approach towards decisions in transient gas networks  |c Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch 
264 1 |a Berlin  |b Zuse Institute Berlin  |c January 4, 2021 
300 |a 1 Online-Ressource (41 Seiten, 2,50 MB)  |b Diagramme 
336 |a Text  |b txt  |2 rdacontent 
337 |a Computermedien  |b c  |2 rdamedia 
338 |a Online-Ressource  |b cr  |2 rdacarrier 
490 1 |a ZIB Report  |v 2020, [38] 
500 |a Literaturverzeichnis: Seite 32-35 
583 1 |a Archivierung/Langzeitarchivierung gewährleistet  |2 pdager  |5 DE-89 
655 7 |a Forschungsbericht  |0 (DE-588)4155043-2  |0 (DE-627)10467444X  |0 (DE-576)209815833  |2 gnd-content 
700 1 |a Turner, Mark  |e VerfasserIn  |4 aut 
700 1 |a Koch, Thorsten  |d 1967-  |e VerfasserIn  |0 (DE-588)129726982  |0 (DE-627)478565437  |0 (DE-576)297806076  |4 aut 
710 2 |a Zuse Institute Berlin  |e Herausgebendes Organ  |0 (DE-588)1084125323  |0 (DE-627)848303865  |0 (DE-576)456176314  |4 isb 
810 2 |a Konrad-Zuse-Zentrum für Informationstechnik Berlin  |t ZIB-Report  |v 2020, [38]  |9 2020,38  |w (DE-627)478815719  |w (DE-576)433876018  |w (DE-600)2176854-7  |x 2192-7782 
856 4 0 |u https://edocs.tib.eu/files/e01fn21/1745974350.pdf  |q application/pdf  |x Verlag  |z kostenfrei  |3 Volltext 
912 |a ZDB-296-TTN 
951 |a BO 
910 |a ZIB 
910 |a Zuse Institut Berlin 
910 |a Konrad-Zuse-Zentrum für Informationstechnik Berlin 
852 |d DE-Zi4  |x epn:4124607784 del:202302250131 
856 4 0 |u https://edocs.tib.eu/files/e01fn21/1745974350.pdf  |9 LFER 
970 |c OD 
971 |c EBOOK 
972 |c EBOOK 
973 |c EB 
935 |a lfer 
852 |a LFER  |x epn:3850888401  |z 2021-02-10T09:00:22Z 
980 |a 1745974350  |b 0  |k 1745974350  |c lfer 
openURL url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=A+generative+deep+learning+approach+towards+decisions+in+transient+gas+networks&rft.date=January+4%2C+2021&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.creator=Anderson%2C+Lovis&rft.pub=Zuse+Institute+Berlin&rft.format=eBook&rft.language=English
SOLR
_version_ 1795510231179984896
author Anderson, Lovis, Turner, Mark, Koch, Thorsten
author_corporate Zuse Institute Berlin
author_corporate_role isb
author_facet Anderson, Lovis, Turner, Mark, Koch, Thorsten, Zuse Institute Berlin
author_role aut, aut, aut
author_sort Anderson, Lovis
author_variant l a la, m t mt, t k tk
collection ZDB-296-TTN, lfer
ctrlnum (DE-627)1745974350, (DE-599)KXP1745974350, (OCoLC)1299238071
facet_912a ZDB-296-TTN
facet_avail Online, Free
footnote Literaturverzeichnis: Seite 32-35
format eBook
format_access_txtF_mv Book, E-Book
format_de105 Ebook
format_de14 Book, E-Book
format_de15 Book, E-Book
format_del152 Buch
format_detail_txtF_mv text-online-monograph-independent
format_dezi4 e-Book
format_finc Book, E-Book
format_legacy ElectronicBook
format_legacy_nrw Book, E-Book
format_nrw Book, E-Book
format_strict_txtF_mv E-Book
genre Forschungsbericht (DE-588)4155043-2 (DE-627)10467444X (DE-576)209815833 gnd-content
genre_facet Forschungsbericht
geogr_code not assigned
geogr_code_person not assigned
hierarchy_parent_id 0-478815719
hierarchy_parent_title Konrad-Zuse-Zentrum für Informationstechnik Berlin: ZIB-Report
hierarchy_sequence 2020,38
hierarchy_top_id 0-478815719
hierarchy_top_title Konrad-Zuse-Zentrum für Informationstechnik Berlin: ZIB-Report
id 0-1745974350
illustrated Not Illustrated
imprint Berlin, Zuse Institute Berlin, January 4, 2021
imprint_str_mv Berlin: Zuse Institute Berlin, January 4, 2021
institution DE-D117, DE-105, LFER, DE-Ch1, DE-15, DE-14, DE-Zwi2
is_hierarchy_id 0-1745974350
is_hierarchy_title A generative deep learning approach towards decisions in transient gas networks
issn_isn_mv 2192-7782
kxp_id_str 1745974350
language English
last_indexed 2024-04-05T15:46:30.636Z
marc_error [geogr_code]Unable to make public java.lang.AbstractStringBuilder java.lang.AbstractStringBuilder.append(java.lang.String) accessible: module java.base does not "opens java.lang" to unnamed module @7838f2f1
match_str anderson2021agenerativedeeplearningapproachtowardsdecisionsintransientgasnetworks
mega_collection Verbunddaten SWB, Lizenzfreie Online-Ressourcen
misc_de105 EBOOK
multipart_link 433876018
multipart_part (433876018)2020, [38]
names_id_str_mv (DE-588)129726982, (DE-627)478565437, (DE-576)297806076, (DE-588)1084125323, (DE-627)848303865, (DE-576)456176314
oclc_num 1299238071
physical 1 Online-Ressource (41 Seiten, 2,50 MB); Diagramme
publishDate January 4, 2021
publishDateSort 2021
publishPlace Berlin
publisher Zuse Institute Berlin
record_format marcfinc
record_id 1745974350
recordtype marcfinc
rvk_facet No subject assigned
series Konrad-Zuse-Zentrum für Informationstechnik Berlin, ZIB-Report, 2020, [38]
series2 ZIB Report ; 2020, [38]
source_id 0
spelling Anderson, Lovis VerfasserIn aut, A generative deep learning approach towards decisions in transient gas networks Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch, Berlin Zuse Institute Berlin January 4, 2021, 1 Online-Ressource (41 Seiten, 2,50 MB) Diagramme, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, ZIB Report 2020, [38], Literaturverzeichnis: Seite 32-35, Archivierung/Langzeitarchivierung gewährleistet pdager DE-89, Forschungsbericht (DE-588)4155043-2 (DE-627)10467444X (DE-576)209815833 gnd-content, Turner, Mark VerfasserIn aut, Koch, Thorsten 1967- VerfasserIn (DE-588)129726982 (DE-627)478565437 (DE-576)297806076 aut, Zuse Institute Berlin Herausgebendes Organ (DE-588)1084125323 (DE-627)848303865 (DE-576)456176314 isb, Konrad-Zuse-Zentrum für Informationstechnik Berlin ZIB-Report 2020, [38] 2020,38 (DE-627)478815719 (DE-576)433876018 (DE-600)2176854-7 2192-7782, https://edocs.tib.eu/files/e01fn21/1745974350.pdf application/pdf Verlag kostenfrei Volltext, DE-Zi4 epn:4124607784 del:202302250131, https://edocs.tib.eu/files/e01fn21/1745974350.pdf LFER, LFER epn:3850888401 2021-02-10T09:00:22Z
spellingShingle Anderson, Lovis, Turner, Mark, Koch, Thorsten, A generative deep learning approach towards decisions in transient gas networks, Konrad-Zuse-Zentrum für Informationstechnik Berlin, ZIB-Report, 2020, [38], Forschungsbericht
title A generative deep learning approach towards decisions in transient gas networks
title_auth A generative deep learning approach towards decisions in transient gas networks
title_full A generative deep learning approach towards decisions in transient gas networks Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch
title_fullStr A generative deep learning approach towards decisions in transient gas networks Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch
title_full_unstemmed A generative deep learning approach towards decisions in transient gas networks Zuse Institut Berlin ; Lovis Anderson, Mark Turner, Thorsten Koch
title_in_hierarchy 2020, [38]. A generative deep learning approach towards decisions in transient gas networks (January 4, 2021)
title_short A generative deep learning approach towards decisions in transient gas networks
title_sort a generative deep learning approach towards decisions in transient gas networks
title_unstemmed A generative deep learning approach towards decisions in transient gas networks
topic Forschungsbericht
topic_facet Forschungsbericht
url https://edocs.tib.eu/files/e01fn21/1745974350.pdf
work_keys_str_mv AT andersonlovis agenerativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT turnermark agenerativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT kochthorsten agenerativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT zuseinstituteberlin agenerativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT andersonlovis generativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT turnermark generativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT kochthorsten generativedeeplearningapproachtowardsdecisionsintransientgasnetworks, AT zuseinstituteberlin generativedeeplearningapproachtowardsdecisionsintransientgasnetworks