The Uncertainty Analysis of Model Results : : A Practical Guide

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Special Collection:e-book
Format: Book
Language:English
Published: Cham : : Springer International Publishing : : Imprint: Springer,, 2018
Edition:1st ed. 2018.
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Online Access:https://doi.org/10.1007/978-3-319-76297-5
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id opac-EUL01-000979410
collection e-book
institution L_200
EUL01
spelling Hofer, Eduard. szerző aut http://id.loc.gov/vocabulary/relators/aut
The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer.
1st ed. 2018.
Cham : Springer International Publishing : Imprint: Springer, 2018
XV, 346 p. 129 illus., 107 illus. in color. online forrás
szöveg txt rdacontent
számítógépes c rdamedia
távoli hozzáférés cr rdacarrier
szövegfájl PDF rda
Preface -- Introduction and necessary distinctions -- Step 1: Search -- Step 2: Quantify -- Step 3: Propagate -- Step 4: Estimate uncertainty -- Step 5: Rank uncertainties -- Step 6: Present the analysis and interpret its results -- Practical execution of the analysis -- Uncertainty analysis when separation of uncertainties is required -- Practical examples -- References -- Subject index.
This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.
Nyomtatott kiadás: ISBN 9783319762968
Nyomtatott kiadás: ISBN 9783319762982
Nyomtatott kiadás: ISBN 9783030094560
Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők.
könyv
e-book
Mathematical statistics. EUL10000079757 Y
Computer simulation. EUL10000093376 Y
Economic theory. EUL10001044656 Y
Environmental sciences. EUL10001072417 Y
System safety. EUL10001074773 Y
Statistical Theory and Methods.
Simulation and Modeling.
Mathematical Modeling and Industrial Mathematics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Math. Appl. in Environmental Science.
Quality Control, Reliability, Safety and Risk.
elektronikus könyv
SpringerLink (Online service) közreadó testület
Online változat https://doi.org/10.1007/978-3-319-76297-5
EUL01
language English
format Book
author Hofer, Eduard., szerző
spellingShingle Hofer, Eduard., szerző
The Uncertainty Analysis of Model Results : A Practical Guide
Mathematical statistics.
Computer simulation.
Economic theory.
Environmental sciences.
System safety.
Statistical Theory and Methods.
Simulation and Modeling.
Mathematical Modeling and Industrial Mathematics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Math. Appl. in Environmental Science.
Quality Control, Reliability, Safety and Risk.
elektronikus könyv
author_facet Hofer, Eduard., szerző
SpringerLink (Online service), közreadó testület
author_corporate SpringerLink (Online service), közreadó testület
author_sort Hofer, Eduard.
title The Uncertainty Analysis of Model Results : A Practical Guide
title_sub A Practical Guide
title_short The Uncertainty Analysis of Model Results :
title_full The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer.
title_fullStr The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer.
title_full_unstemmed The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer.
title_auth The Uncertainty Analysis of Model Results : A Practical Guide
title_sort uncertainty analysis of model results a practical guide
publishDate 2018
publishDateSort 2018
physical XV, 346 p. 129 illus., 107 illus. in color. : online forrás
edition 1st ed. 2018.
isbn 978-3-319-76297-5
callnumber-first Q - Science
callnumber-subject QA - Mathematics
callnumber-label QA276-280
callnumber-raw 979410
callnumber-search 979410
topic Mathematical statistics.
Computer simulation.
Economic theory.
Environmental sciences.
System safety.
Statistical Theory and Methods.
Simulation and Modeling.
Mathematical Modeling and Industrial Mathematics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Math. Appl. in Environmental Science.
Quality Control, Reliability, Safety and Risk.
elektronikus könyv
topic_facet Mathematical statistics.
Computer simulation.
Economic theory.
Environmental sciences.
System safety.
Statistical Theory and Methods.
Simulation and Modeling.
Mathematical Modeling and Industrial Mathematics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Math. Appl. in Environmental Science.
Quality Control, Reliability, Safety and Risk.
elektronikus könyv
Mathematical statistics.
Computer simulation.
Economic theory.
Environmental sciences.
System safety.
Statistical Theory and Methods.
Simulation and Modeling.
Mathematical Modeling and Industrial Mathematics.
Economic Theory/Quantitative Economics/Mathematical Methods.
Math. Appl. in Environmental Science.
Quality Control, Reliability, Safety and Risk.
url https://doi.org/10.1007/978-3-319-76297-5
illustrated Not Illustrated
dewey-hundreds 500 - Science
dewey-tens 510 - Mathematics
dewey-ones 519 - Probabilities & applied mathematics
dewey-full 519.5
dewey-sort 3519.5
dewey-raw 519.5
dewey-search 519.5
first_indexed 2023-12-26T23:12:44Z
last_indexed 2023-12-29T19:17:07Z
recordtype opac
publisher Cham : : Springer International Publishing : : Imprint: Springer,
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score 13,368518
generalnotes This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.