Modelling under risk and uncertainty: an introduction to statistical, phenomenological and computational methods

by Rocquigny, Etienne de

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"This volume addresses a concern of very high relevance and growing interest for large industries or environmentalists: risk and uncertainty in complex systems. It gives new insight on the peculiar mathematical challenges generated by recent industrial safety or environmental control analysis, focusing on implementing decision theory choices related to risk and uncertainty analysis through statistical estimation and computation, in the presence of physical modeling and risk analysis. The result…

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Title Statements

  • Full title :Modelling under risk and uncertainty : an introduction to statistical, phenomenological and computational methods / Etienne de Rocquigny.

Summary

"This volume addresses a concern of very high relevance and growing interest for large industries or environmentalists: risk and uncertainty in complex systems. It gives new insight on the peculiar mathematical challenges generated by recent industrial safety or environmental control analysis, focusing on implementing decision theory choices related to risk and uncertainty analysis through statistical estimation and computation, in the presence of physical modeling and risk analysis. The result will lead statisticians and associated professionals to formulate and solve new challenges at the frontier between statistical modeling, physics, scientific computing, and risk analysis"--

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Edition Statements

  • Publication Date:2012.

Publication Statements

  • Publisher(s):Wiley
  • Place of Publication:Chichester, West Sussex, U.K
  • Language:eng
  • Publication Date:2012.

Notes

Titre de l'écran-titre (visionné le 7 févr. 2014).

TRAITEMENT SOMMAIRE.

The Physical Object

  • Description:1 ressource en ligne (xxxviii, 434 p.).

Edition Identifiers

  • oclc:ocn863688695
  • LC Classification:HD30.25
  • Dewey Decimal:338.501/5195

Table of Contents

Applications and practices of modelling, risk and uncertainty -- A generic modelling framework -- A generic tutorial example: natural risk in an industrial installation -- Understanding natures of uncertainty, risk margins and time bases for probabilistic decision-making -- Direct statistical estimation techniques -- Combined model estimation through inverse techniques -- Computational methods for risk and uncertainty propagation -- Optimising under uncertainty: economics and computational challenges -- Conclusion: perspectives of modelling in the context of risk and uncertainty and further research.

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Subjects

Gestion d'entreprise -- Modèles mathéma… Gestion du risque -- Modèles mathématiq… Incertitude -- Modèles mathématiques Industrial management -- Mathematical m… Livres électroniques Risk management -- Mathematical models Uncertainty -- Mathematical models

Writers

Rocquigny, Etienne de

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