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Coping with Uncertainty

Modeling and Policy Issues

  • Conference proceedings
  • © 2006

Overview

Authors:
  1. Kurt Marti

    1. Aero Space Engineering and Technology, Federal Armed Forces University Munich, Neubiberg/Munich, Germany

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  2. Yuri Ermoliev

    1. International Institute for Applied System Analysis, Laxenburg, Austria

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  3. Marek Makowski

    1. International Institute for Applied System Analysis, Laxenburg, Austria

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  4. Georg Pflug

    1. Institute for Statistics and Informatics, University of Vienna, Vienna, Austria

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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 581)

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Table of contents (18 papers)

  1. Front Matter

    Pages I-XIII
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  2. Uncertainty and Decisions

    1. Front Matter

      Pages 1-1
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    2. Facets of Robust Decisions

      • Y. Ermoliev, L. Hordijk
      Pages 3-28

    3. Stress Testing via Contamination

      • J. Dupačová
      Pages 29-46

    4. Structured Modeling for Coping with Uncertainty in Complex Problems

      • M. Makowski
      Pages 47-64

  3. Modeling Stochastic Uncertainty

    1. Front Matter

      Pages 65-65
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    2. Using Monte Carlo Simulation to Treat Physical Uncertainties in Structural Reliability

      • D. C. Charmpis, G. I. Schuëller
      Pages 67-83

    3. Explicit Methods for the Computation of Structural Reliabilities in Stochastic Plastic Analysis

      • I. Kaymaz, K. Marti
      Pages 85-103

    4. Statistical Analysis of Catastrophic Events

      • J. L. Teugels, B. Vandewalle
      Pages 105-117

    5. Scene Interpretation Using Bayesian Network Fragments

      • P. Lueders
      Pages 119-130

  4. Non-Probabilistic Uncertainty

    1. Front Matter

      Pages 131-131
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    2. General Equilibrium Models with Discrete Choices in a Spatial Continuum

      • M. Keyzer, Y. Ermoliev, V. Norkin
      Pages 133-154

    3. Sequential Downscaling Methods for Estimation from Aggregate Data

      • G. Fischer, T. Ermolieva, Y. Ermoliev, H. Van Velthuizen
      Pages 155-169

    4. Optimal Control for a Class of Uncertain Systems

      • F. L. Chernousko
      Pages 171-183

    5. Uncertainties in Medical Processes Control

      • A. G. Nakonechny, V. P. Marzeniuk
      Pages 185-192

  5. Applications of Stochastic Optimization

    1. Front Matter

      Pages 193-193
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    2. Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change: A Stochastic Optimization Approach

      • A. Gritsevskyi, H. -H. Rogner
      Pages 195-216

    3. Stochasticity in Electric Energy Systems Planning

      • A. Ramos, S. Cerisola, Á. Baíllo, J. M. Latorre
      Pages 217-239

    4. Stochastic Programming Based PERT Modeling

      • A. Gouda, D. Monhor, T. Szántai
      Pages 241-255

    5. Towards Implementable Nonlinear Stochastic Programming

      • L. Sakalauskas
      Pages 257-279
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Keywords

About this book

Ongoing global changes bring fundamentally new scientific problems requiring new concepts and tools. A key issue concerns a vast variety of practically irreducible uncertainties, which challenge our traditional models and require new concepts and analytical tools. The uncertainty critically dominantes, e.g., the climate change debates. In short, the dilemma is concerned with enormous costs vs. massive uncertainties of potential extreme impacts. Traditional scientific approaches usually rely on real observations and experiments. Yet no sufficient observations exist for new problems, and "pure" experiments and learning by doing may be very expensive, dangerous, or simply impossible. In addition, available historical observations are contaminated by actions, policies. The complexity of new problems does not allow to achieve enough certainty by increasing the resolution of models or by bringing in more links. Hence, new tools for modeling and management of uncertainty are needed, as given in this book.

Authors and Affiliations

  • Aero Space Engineering and Technology, Federal Armed Forces University Munich, Neubiberg/Munich, Germany

    Kurt Marti

  • International Institute for Applied System Analysis, Laxenburg, Austria

    Yuri Ermoliev, Marek Makowski

  • Institute for Statistics and Informatics, University of Vienna, Vienna, Austria

    Georg Pflug

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