Shows how global changes pose urgent, fundamentally new scientific problems
Presents much-needed tools for modeling and management of complex problems
Offers action-oriented strategy for dealing with complex, large scale problems
Ongoing global changes pose fundamentally new scientific problems requiring new concepts and tools. A key issue concerns a vast variety of practically irreducible uncertainties, which challenge traditional models and require new concepts and analytical tools. Uncertainty can dominate, as in the climate change debates. Increasing the resolution of models does not always yield sufficient certainty. This book presents much-needed new tools for modeling and management of uncertainty.
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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 dominates, 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 which was prepared for an interdisciplinary audience, and addresses open
problems, limitations of known approaches, novel methods and techniques, or lessons
from the applications of various approaches. Thus, the book contributes to a better
understanding between practitioners dealing with the management of uncertainty, and
scientists working on either corresponding modeling approaches that can be applied for
improving understanding or management of uncertainty.
Uncertainty and Decisions: Facets of Robust Decisions.- Stress Testing via Contamination.- Structured Modeling for Coping with Uncertainty in Complex Problems.- Modeling Stochastic Uncertainty: Using Monte Carlo Simulation to Treat Physical Uncertainties in Structural Reliability.- Explicit Methods for the Computation of Strucutral Reliabilities in Stochastic Plastic Analysis.- Statistical Analysis of Catastrophie Events.- Scene Interpretation Using Bayesian Network Fragments.- Non-probabilistic Uncertainty: General Equilibrium Models with Discrete Choices in a Spatial Continuum.- Sequential Downscaling Methods for Estimation from Aggregate Data.- Optimal Control for a Class of Uncertain Systems.- Uncertainties in Medical Processes Control.- Applications of Stochastic Optimization: Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change. A Stochastic Optimization Appraoch.- Stochasticity in Electric Energy Systems Planning.- Stochastic Programming Based PERT Modeling.- Towards Implementable Nonlinear Stochastic Programming.- Policy Issues Under Uncertainty: Endogenous Risks and Learning.- Pricing Related Projects.- Precaution. The Willingness to Accept Costs to Avert Uncertain Danger
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.
Uncertainty and Decisions.- Facets of Robust Decisions.- Stress Testing via Contamination.- Structured Modeling for Coping with Uncertainty in Complex Problems.- Modeling Stochastic Uncertainty.- Using Monte Carlo Simulation to Treat Physical Uncertainties in Structural Reliability.- Explicit Methods for the Computation of Structural Reliabilities in Stochastic Plastic Analysis.- Statistical Analysis of Catastrophic Events.- Scene Interpretation Using Bayesian Network Fragments.- Non-Probabilistic Uncertainty.- General Equilibrium Models with Discrete Choices in a Spatial Continuum.- Sequential Downscaling Methods for Estimation from Aggregate Data.- Optimal Control for a Class of Uncertain Systems.- Uncertainties in Medical Processes Control.- Applications of Stochastic Optimization.- Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change: A Stochastic Optimization Approach.- Stochasticity in Electric Energy Systems Planning.- Stochastic Programming Based PERT Modeling.- Towards Implementable Nonlinear Stochastic Programming.- Policy Issues Under Uncertainty.- Endogenous Risks and Learning in Climate Change Decision Analysis.- Pricing Related Projects.- Precaution: The Willingness to Accept Costs to Avert Uncertain Danger.
Kurt Marti, geb. 1921 in Bern, Studium der Jura, dann Theologie in Bern und Basel. Bis 1983 tätig als Pfarrer, u. a. an der Nydeggkirche in Bern. Er ist Ehrendoktor der theologischen Fakultät Bern, Mitbegründer der Schriftsteller-Gruppe Olten und der Erklärung von Bern. Zahlreiche Veröffentlichungen: Erzählungen, einen Roman, Gedichte, Tagebücher, Essays. Auszeichnungen: 1997 Kurt-Tucholsky-Preis für sein Gesamtwerk, 2002 Karl-Barth-Preis für sein'"theopoetisches' Werk.
Inhaltsverzeichnis
Uncertainty and Decisions: Facets of Robust Decisions.- Stress Testing via Contamination.- Structured Modeling for Coping with Uncertainty in Complex Problems.- Modeling Stochastic Uncertainty: Using Monte Carlo Simulation to Treat Physical Uncertainties in Structural Reliability.- Explicit Methods for the Computation of Strucutral Reliabilities in Stochastic Plastic Analysis.- Statistical Analysis of Catastrophie Events.- Scene Interpretation Using Bayesian Network Fragments.- Non-probabilistic Uncertainty: General Equilibrium Models with Discrete Choices in a Spatial Continuum.- Sequential Downscaling Methods for Estimation from Aggregate Data.- Optimal Control for a Class of Uncertain Systems.- Uncertainties in Medical Processes Control.- Applications of Stochastic Optimization: Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change. A Stochastic Optimization Appraoch.- Stochasticity in Electric Energy Systems Planning.- Stochastic Programming Based PERT Modeling.- Towards Implementable Nonlinear Stochastic Programming.- Policy Issues Under Uncertainty: Endogenous Risks and Learning.- Pricing Related Projects.- Precaution. The Willingness to Accept Costs to Avert Uncertain Danger
Klappentext
Ongoing global changes pose fundamentally new scientific problems requiring new concepts and tools. A key issue concerns a vast variety of practically irreducible uncertainties, which challenge traditional models and require new concepts and analytical tools. Uncertainty can dominate, as in the climate change debates. Increasing the resolution of models does not always yield sufficient certainty. This book presents much-needed new tools for modeling and management of uncertainty.
Shows how global changes pose urgent, fundamentally new scientific problems
Presents much-needed tools for modeling and management of complex problems
Offers action-oriented strategy for dealing with complex, large scale problems
