A great many problems in natural, technical, and social sciences can be solved by means of suitable mathematical models. Since the input data of mathematical models is uncertain, the output values are also encubered by uncertainty. It is our goal to evaluate the uncertainty of output data if the uncertainty of input data is somehow speci ed. Here, we con- ne ourselves only to a brief description of stochastic methods, a fuzzy set approach, and the worst scenario method
summary:In practice, input data entering a state problem are almost always uncertain to some extent....
In this chapter, we are concerned with decision making methods for dynamic systems under uncertainty...
Optimization is of central concern to a number of discip lines. Operations Research and Decision Th...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
Inputs entering a mathematical model are considered uncertain, i.e., they are not given in a crisp f...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
In this contribution, the worst scenario method is applied to problem described by nonlinear differe...
There exist techniques for decision making under specific types of uncertainty, such as probabilisti...
Uncertainties enter into a complex problem from many sources: variability, errors, and lack of knowl...
Recent developments in Soft Computing and StatisticsInternational audienceProbability theory has bee...
AbstractUncertainty is everywhere, and there are many researches on uncertain problems. Soft Computi...
summary:In practice, input data entering a state problem are almost always uncertain to some extent....
In this chapter, we are concerned with decision making methods for dynamic systems under uncertainty...
Optimization is of central concern to a number of discip lines. Operations Research and Decision Th...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
Inputs entering a mathematical model are considered uncertain, i.e., they are not given in a crisp f...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
summary:An introduction to the worst scenario method is given. We start with an example and a genera...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
summary:The goal of this contribution is to introduce some approaches to uncertainty modeling in a w...
In this contribution, the worst scenario method is applied to problem described by nonlinear differe...
There exist techniques for decision making under specific types of uncertainty, such as probabilisti...
Uncertainties enter into a complex problem from many sources: variability, errors, and lack of knowl...
Recent developments in Soft Computing and StatisticsInternational audienceProbability theory has bee...
AbstractUncertainty is everywhere, and there are many researches on uncertain problems. Soft Computi...
summary:In practice, input data entering a state problem are almost always uncertain to some extent....
In this chapter, we are concerned with decision making methods for dynamic systems under uncertainty...
Optimization is of central concern to a number of discip lines. Operations Research and Decision Th...