Simulation:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam
Academic Press
2013
|
| Ausgabe: | Fifth edition |
| Schlagworte: | |
| Beschreibung: | Print version record |
| Beschreibung: | 1 online resource (xii, 310 pages) illustrations |
| ISBN: | 0124159710 9780124159716 |
Internformat
MARC
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| 100 | 1 | |a Ross, Sheldon M. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Simulation |c Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California |
| 250 | |a Fifth edition | ||
| 264 | 1 | |a Amsterdam |b Academic Press |c 2013 | |
| 300 | |a 1 online resource (xii, 310 pages) |b illustrations | ||
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| 505 | 8 | |a "In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"-- | |
| 650 | 7 | |a MATHEMATICS / Probability & Statistics / General |2 bisacsh | |
| 650 | 7 | |a Computer simulation |2 fast | |
| 650 | 7 | |a Probabilities |2 fast | |
| 650 | 7 | |a Random variables |2 fast | |
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| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Ross, Sheldon M. |t Simulation |b Fifth edition |z 9780124158252 |
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Datensatz im Suchindex
| _version_ | 1804179173954027520 |
|---|---|
| any_adam_object | |
| author | Ross, Sheldon M. |
| author_facet | Ross, Sheldon M. |
| author_role | aut |
| author_sort | Ross, Sheldon M. |
| author_variant | s m r sm smr |
| building | Verbundindex |
| bvnumber | BV045349783 |
| classification_rvk | SK 820 ST 340 |
| collection | ZDB-4-ITC |
| contents | "In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"-- |
| ctrlnum | (ZDB-4-ITC)ocn818733978 (OCoLC)818733978 (DE-599)BVBBV045349783 |
| dewey-full | 519.2 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.2 |
| dewey-search | 519.2 |
| dewey-sort | 3519.2 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| edition | Fifth edition |
| format | Electronic eBook |
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| id | DE-604.BV045349783 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:15:40Z |
| institution | BVB |
| isbn | 0124159710 9780124159716 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030736437 |
| oclc_num | 818733978 |
| open_access_boolean | |
| physical | 1 online resource (xii, 310 pages) illustrations |
| psigel | ZDB-4-ITC |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Academic Press |
| record_format | marc |
| spelling | Ross, Sheldon M. Verfasser aut Simulation Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California Fifth edition Amsterdam Academic Press 2013 1 online resource (xii, 310 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Print version record "In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"-- MATHEMATICS / Probability & Statistics / General bisacsh Computer simulation fast Probabilities fast Random variables fast Random variables Probabilities Computer simulation Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf Simulation (DE-588)4055072-2 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s Computersimulation (DE-588)4148259-1 s Monte-Carlo-Simulation (DE-588)4240945-7 s 1\p DE-604 Simulation (DE-588)4055072-2 s 2\p DE-604 Erscheint auch als Druck-Ausgabe Ross, Sheldon M. Simulation Fifth edition 9780124158252 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Ross, Sheldon M. Simulation "In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"-- MATHEMATICS / Probability & Statistics / General bisacsh Computer simulation fast Probabilities fast Random variables fast Random variables Probabilities Computer simulation Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Simulation (DE-588)4055072-2 gnd Computersimulation (DE-588)4148259-1 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| subject_GND | (DE-588)4064324-4 (DE-588)4055072-2 (DE-588)4148259-1 (DE-588)4240945-7 |
| title | Simulation |
| title_auth | Simulation |
| title_exact_search | Simulation |
| title_full | Simulation Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California |
| title_fullStr | Simulation Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California |
| title_full_unstemmed | Simulation Sheldon M. Ross, Epstein Department of Industrial and Systems Engineering, University of Southern California |
| title_short | Simulation |
| title_sort | simulation |
| topic | MATHEMATICS / Probability & Statistics / General bisacsh Computer simulation fast Probabilities fast Random variables fast Random variables Probabilities Computer simulation Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Simulation (DE-588)4055072-2 gnd Computersimulation (DE-588)4148259-1 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| topic_facet | MATHEMATICS / Probability & Statistics / General Computer simulation Probabilities Random variables Random variables Probabilities Computer simulation Wahrscheinlichkeitsrechnung Simulation Computersimulation Monte-Carlo-Simulation |
| work_keys_str_mv | AT rosssheldonm simulation |