|
|
|
|
LEADER |
03011cam a2200601 4500 |
001 |
183-1751434168 |
003 |
DE-627 |
005 |
20220107111637.0 |
007 |
tu |
008 |
210316s2021 gw ||||| m 00| ||eng c |
035 |
|
|
|a (DE-627)1751434168
|
035 |
|
|
|a (DE-599)KXP1751434168
|
035 |
|
|
|a (OCoLC)1241732931
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rda
|
041 |
|
|
|a eng
|a ger
|
044 |
|
|
|c XA-DE-HH
|
082 |
0 |
4 |
|a 530
|a 004
|q DE-101
|
084 |
|
|
|a 33.06
|2 bkl
|
084 |
|
|
|a 33.50
|2 bkl
|
084 |
|
|
|a 54.72
|2 bkl
|
088 |
|
|
|a DESY-THESIS-2021-001
|
100 |
1 |
|
|a Bayat Makou, M.
|e VerfasserIn
|0 (DE-588)1229450920
|0 (DE-627)1751434729
|4 aut
|
245 |
1 |
0 |
|a Optimizing the machine learning techniques in the H → ττ analysis with CMS data
|c by M. Bayat Makou
|
264 |
|
1 |
|a Hamburg
|b Deutsches Elektronen-Synchrotron, DESY
|c February 2021
|
300 |
|
|
|a i, 77 Seiten
|b Illustrationen, Diagramme
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
|
338 |
|
|
|a Band
|b nc
|2 rdacarrier
|
490 |
1 |
|
|a DESY thesis
|v 2021, 001
|
500 |
|
|
|a Literaturverzeichnis: Seite 77-80
|
502 |
|
|
|b Masterarbeit
|c Universität Hamburg
|d 2021
|
546 |
|
|
|a Zusammenfassung in deutscher und englischer Sprache
|
583 |
1 |
|
|a Archivierung/Langzeitarchivierung gewährleistet
|c 2021
|f PEHH
|2 pdager
|5 DE-18
|
655 |
|
7 |
|a Hochschulschrift
|0 (DE-588)4113937-9
|0 (DE-627)105825778
|0 (DE-576)209480580
|2 gnd-content
|
689 |
0 |
0 |
|D s
|0 (DE-588)4398783-7
|0 (DE-627)191678511
|0 (DE-576)212030167
|a LHC
|2 gnd
|
689 |
0 |
1 |
|D s
|0 (DE-588)4664064-2
|0 (DE-627)338127275
|0 (DE-576)214797511
|a CMS-Detektor
|2 gnd
|
689 |
0 |
2 |
|D s
|0 (DE-588)4209328-4
|0 (DE-627)105105325
|0 (DE-576)210191414
|a Higgs-Teilchen
|2 gnd
|
689 |
0 |
3 |
|D s
|0 (DE-588)4067675-4
|0 (DE-627)10445900X
|0 (DE-576)209170859
|a Zerfall
|2 gnd
|
689 |
0 |
4 |
|D s
|0 (DE-588)4233855-4
|0 (DE-627)104914076
|0 (DE-576)210375744
|a Tauon
|2 gnd
|
689 |
0 |
5 |
|D s
|0 (DE-588)4193754-5
|0 (DE-627)105224782
|0 (DE-576)21008944X
|a Maschinelles Lernen
|2 gnd
|
689 |
0 |
|
|5 (DE-627)
|
710 |
2 |
|
|a Universität Hamburg
|e Grad-verleihende Institution
|0 (DE-588)35534-3
|0 (DE-627)100820204
|0 (DE-576)190340177
|4 dgg
|
751 |
|
|
|a Hamburg
|0 (DE-588)4023118-5
|0 (DE-627)106305433
|0 (DE-576)20894754X
|4 uvp
|
810 |
2 |
|
|a Deutsches Elektronen-Synchrotron
|t DESY thesis
|v 2021, 001
|9 2021,1
|w (DE-627)246827939
|w (DE-576)065726251
|w (DE-600)1437131-5
|x 1435-8085
|7 ns
|
856 |
4 |
2 |
|u https://www.gbv.de/dms/tib-ub-hannover/1751434168.pdf
|m V:DE-601
|m B:DE-89
|q pdf/application
|3 Inhaltsverzeichnis
|
856 |
4 |
2 |
|u https://bib-pubdb1.desy.de/record/455392
|q application
|y Inhaltsbeschreibung & PDF-Volltext
|
924 |
0 |
|
|a 388917258X
|b DE-18
|9 18
|c GBV
|d c
|g B/200717
|h SUB
|
924 |
0 |
|
|a 3940763950
|b DE-89
|9 89
|c GBV
|d c
|g RR 8919(2021,1)
|
936 |
b |
k |
|a 33.06
|j Mathematische Methoden der Physik
|0 (DE-627)106407937
|
936 |
b |
k |
|a 33.50
|j Physik der Elementarteilchen und Felder: Allgemeines
|0 (DE-627)10640749X
|
936 |
b |
k |
|a 54.72
|j Künstliche Intelligenz
|0 (DE-627)10641240X
|
951 |
|
|
|a BO
|
980 |
|
|
|a 1751434168
|b 183
|c sid-183-col-kxpbbi
|
SOLR
_version_ |
1797788662727966720 |
author |
Bayat Makou, M. |
author_corporate |
Universität Hamburg |
author_corporate_role |
dgg |
author_facet |
Bayat Makou, M., Universität Hamburg |
author_role |
aut |
author_sort |
Bayat Makou, M. |
author_variant |
m m b mm mmb |
building |
Library A |
collection |
sid-183-col-kxpbbi |
ctrlnum |
(DE-627)1751434168, (DE-599)KXP1751434168, (OCoLC)1241732931 |
dewey-full |
530, 004 |
dewey-hundreds |
500 - Natural sciences and mathematics, 000 - Computer science, information, general works |
dewey-ones |
530 - Physics, 004 - Computer science |
dewey-raw |
530, 004 |
dewey-search |
530, 004 |
dewey-sort |
3530 |
dewey-tens |
530 - Physics, 000 - Computer science, information, general works |
facet_avail |
Local |
facet_local_del330 |
LHC, CMS-Detektor, Higgs-Teilchen, Zerfall, Tauon, Maschinelles Lernen |
finc_class_facet |
Physik, Informatik |
fincclass_txtF_mv |
science-physics, science-computerscience |
footnote |
Literaturverzeichnis: Seite 77-80 |
format |
Book, Thesis |
format_access_txtF_mv |
Thesis |
format_de14 |
Book, E-Book |
format_de15 |
Book, E-Book |
format_del152 |
Buch |
format_detail_txtF_mv |
text-print-monograph-independent-thesis |
format_dezi4 |
e-Book |
format_finc |
Book, E-Book, Thesis |
format_legacy |
Book |
format_legacy_nrw |
Book, E-Book |
format_nrw |
Book, E-Book |
format_strict_txtF_mv |
Thesis |
genre |
Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content |
genre_facet |
Hochschulschrift |
geogr_code |
not assigned |
geogr_code_person |
not assigned |
hierarchy_parent_id |
183-246827939 |
hierarchy_parent_title |
Deutsches Elektronen-Synchrotron: DESY thesis |
hierarchy_sequence |
2021,1 |
hierarchy_top_id |
183-246827939 |
hierarchy_top_title |
Deutsches Elektronen-Synchrotron: DESY thesis |
id |
183-1751434168 |
illustrated |
Not Illustrated |
imprint |
Hamburg, Deutsches Elektronen-Synchrotron, DESY, February 2021 |
imprint_str_mv |
Hamburg: Deutsches Elektronen-Synchrotron, DESY, February 2021 |
institution |
FID-BBI-DE-23 |
is_hierarchy_id |
183-1751434168 |
is_hierarchy_title |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data |
issn_isn_mv |
1435-8085 |
language |
English, German |
last_indexed |
2024-04-30T19:21:12.422Z |
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 @64e01542 |
match_str |
bayatmakou2021optimizingthemachinelearningtechniquesinthehttanalysiswithcmsdata |
mega_collection |
K10plus Verbundkatalog |
multipart_link |
065726251 |
multipart_part |
(065726251)2021, 001 |
oclc_num |
1241732931 |
physical |
i, 77 Seiten; Illustrationen, Diagramme |
publishDate |
February 2021 |
publishDateSort |
2021 |
publishPlace |
Hamburg |
publisher |
Deutsches Elektronen-Synchrotron, DESY |
record_format |
marcfinc |
record_id |
1751434168 |
recordtype |
marcfinc |
rvk_facet |
No subject assigned |
series |
Deutsches Elektronen-Synchrotron, DESY thesis, 2021, 001 |
series2 |
DESY thesis ; 2021, 001 |
source_id |
183 |
spelling |
Bayat Makou, M. VerfasserIn (DE-588)1229450920 (DE-627)1751434729 aut, Optimizing the machine learning techniques in the H → ττ analysis with CMS data by M. Bayat Makou, Hamburg Deutsches Elektronen-Synchrotron, DESY February 2021, i, 77 Seiten Illustrationen, Diagramme, Text txt rdacontent, ohne Hilfsmittel zu benutzen n rdamedia, Band nc rdacarrier, DESY thesis 2021, 001, Literaturverzeichnis: Seite 77-80, Masterarbeit Universität Hamburg 2021, Zusammenfassung in deutscher und englischer Sprache, Archivierung/Langzeitarchivierung gewährleistet 2021 PEHH pdager DE-18, Hochschulschrift (DE-588)4113937-9 (DE-627)105825778 (DE-576)209480580 gnd-content, s (DE-588)4398783-7 (DE-627)191678511 (DE-576)212030167 LHC gnd, s (DE-588)4664064-2 (DE-627)338127275 (DE-576)214797511 CMS-Detektor gnd, s (DE-588)4209328-4 (DE-627)105105325 (DE-576)210191414 Higgs-Teilchen gnd, s (DE-588)4067675-4 (DE-627)10445900X (DE-576)209170859 Zerfall gnd, s (DE-588)4233855-4 (DE-627)104914076 (DE-576)210375744 Tauon gnd, s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd, (DE-627), Universität Hamburg Grad-verleihende Institution (DE-588)35534-3 (DE-627)100820204 (DE-576)190340177 dgg, Hamburg (DE-588)4023118-5 (DE-627)106305433 (DE-576)20894754X uvp, Deutsches Elektronen-Synchrotron DESY thesis 2021, 001 2021,1 (DE-627)246827939 (DE-576)065726251 (DE-600)1437131-5 1435-8085 ns, https://www.gbv.de/dms/tib-ub-hannover/1751434168.pdf V:DE-601 B:DE-89 pdf/application Inhaltsverzeichnis, https://bib-pubdb1.desy.de/record/455392 application Inhaltsbeschreibung & PDF-Volltext |
spellingShingle |
Bayat Makou, M., Optimizing the machine learning techniques in the H → ττ analysis with CMS data, Deutsches Elektronen-Synchrotron, DESY thesis, 2021, 001, Hochschulschrift, LHC, CMS-Detektor, Higgs-Teilchen, Zerfall, Tauon, Maschinelles Lernen |
title |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data |
title_auth |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data |
title_full |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data by M. Bayat Makou |
title_fullStr |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data by M. Bayat Makou |
title_full_unstemmed |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data by M. Bayat Makou |
title_in_hierarchy |
2021, 001. Optimizing the machine learning techniques in the H → ττ analysis with CMS data (February 2021) |
title_short |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data |
title_sort |
optimizing the machine learning techniques in the h → ττ analysis with cms data |
title_unstemmed |
Optimizing the machine learning techniques in the H → ττ analysis with CMS data |
topic |
Hochschulschrift, LHC, CMS-Detektor, Higgs-Teilchen, Zerfall, Tauon, Maschinelles Lernen |
topic_facet |
Hochschulschrift, LHC, CMS-Detektor, Higgs-Teilchen, Zerfall, Tauon, Maschinelles Lernen |
url |
https://www.gbv.de/dms/tib-ub-hannover/1751434168.pdf, https://bib-pubdb1.desy.de/record/455392 |
work_keys_str_mv |
AT bayatmakoum optimizingthemachinelearningtechniquesinthehttanalysiswithcmsdata, AT universitathamburg optimizingthemachinelearningtechniquesinthehttanalysiswithcmsdata |