Managing safety of diverse systems requires decision-making
under uncertainties and risks. Such systems are typically
characterized by spatio-temporal heterogeneities,
inter-dependencies, externalities, endogenous risks,
discontinuities, irreversibility, practically irreducible
uncertainties, and rare events with catastrophic consequences.
Traditional scientific approaches rely on data from real
observations and experiments; yet no sufficient observations exist
for new problems, and experiments are usually impossible.
Therefore, science-based support for addressing such new class of
problems needs to replace the traditional "deterministic
predictions" analysis by new methods and tools for designing
decisions that are robust against the involved uncertainties and
risks. The new methods treat uncertainties explicitly by using
"synthetic" information derived by integration of "hard" elements,
including available data, results of possible experiments, and
formal representations of scientific facts, with "soft" elements
based on diverse representations of scenarios and opinions of
public, stakeholders, and experts. The volume presents such
effective new methods, and illustrates their applications in
different problem areas, including engineering, economy, finance,
agriculture, environment, and policy making.
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