Titlebook: Coping with Uncertainty; Modeling and Policy Kurt Marti,Yuri Ermoliev,Georg Pflug Conference proceedings 2006 Springer-Verlag Berlin Heide

endoscopy

Obstacle

Scene Interpretation Using Bayesian Network Fragments and describe an interpretation method exploiting these. The approach offers arbitrary reasoning facilities, where low level perceptive information as well as abstract context knowledge within scenes can be either given as evidence or queried.

Pandemic

Optimal Control for a Class of Uncertain Systemsimax control problem is formulated and solved. The explicit expressions for the optimal control (both open-loop and feedback) are obtained that provide the minimax to the given performance index for arbitrary but bounded disturbances. Examples are given.

aviator

Impacts of Uncertainty and Increasing Returns on Sustainable Energy Development and Climate Change: le stochastic optimization model requiring special global optimization technique which takes advantage of the specific structure of the problem..This article primarily concentrated with main motivations, critical importance of non-convexity (increasing returns) and explicit treatment of uncertainty by using stochastic optimization approach.

否決

Stochasticity in Electric Energy Systems Planninging process in electric companies. A unit commitment, a market-based unit commitment, a hydrothermal coordination and a risk management model are typical models that can incorporate uncertainty in the decision framework.

串通

抓住他投降

Notes from the Trial of the Century,natural catastrophes. Together these sets should provide ample proof that extreme value analysis might be able to catch some essential information that traditional statistical analysis might overlook. We finish with a number of cautious remarks.

Uncultured

Notes from the Trial of the Century, practice. The focus of this chapter is on statistically high-dimensional problems, which involve large numbers of random variables. The merits of some of the techniques and algorithms described are demonstrated with two application examples.

古董

套索

Using Monte Carlo Simulation to Treat Physical Uncertainties in Structural Reliability practice. The focus of this chapter is on statistically high-dimensional problems, which involve large numbers of random variables. The merits of some of the techniques and algorithms described are demonstrated with two application examples.