The paper extends the recently developed robust LQG control design methodology to stochastic uncertain systems with a normalised coprime factor uncertainty structure. To consider this class of model uncertainties, a special technique of probability measure transformations is developed. As a by-product, other types of the model uncertainty, for example, those reflecting passivity of the uncertai...

Global challenge and the speedy growth of information technologies compel organizations to constantly change their ways. At the present time, associations need IT personnel who create a difference by creative thoughts and who preserve with the rapid amendments. Since the evaluation of IT personnel selection (ITPS) consists of different alternatives and criteria, therefore, IT personnel selectio...

The option-pricing problem is always an important part in modern finance. Assuming that the stock diffusion is a constant, some literature has introduced many stock models and given corresponding option pricing formulas within the framework of the uncertainty theory. In this paper, we propose a new stock model with uncertain stock diffusion for uncertain markets. Some option pricing formulas on...

Knightian uncertainty differs from risk in that it describes situations where randomness of an uncertain event faced by a decision maker cannot be adequately described by a probability measure. This paper reviews the recent advancements in the theory of choice under Knightian uncertainty and their applications in economics and finance.

We consider a two-stage mixed integer stochastic optimization problem and show that a static robust solution is a good approximation to the fully adaptable two-stage solution for the stochastic problem under fairly general assumptions on the uncertainty set and the probability distribution. In particular, we show that if the right-hand side of the constraints is uncertain and belongs to a symme...

A novel sensor failure detection method is developed in this paper. Sensor failure considered in this paper can be any type of measurement error that is different from the true structural response. The sensors are divided into two groups; sensors that correctly measure the structural responses are termed “reference sensors” and sensors that may fail to correctly measure the structural responses...

Markov Decision Processes (MDPs) model problems of sequential decision-nmaking under uncertainty. They have been studied and applied extensively. Nonetheless, there are two major barriers that still hinder the applicability of MDPs to many more practical decision making problems: * The decision maker is often lacking a reliable MDP model. Since the results obtained by dynamic programming are se...

Introduction captured by our uncertainty calculi. Finally Cij is the The purpose this work is to discuss and investigate payoff to the decision maker if he selects alternative Ai the potential role of possibility theory [1-4] and other and V assumes the value Xj. One approach for non-standard uncertainty calculi, such as the Dempsterselecting the best alternative in this decision problem is Sha...

this paper concerns the problem of robust stabilization of uncertain fractional-order non-autonomous systems. in this regard, a single input active control approach is proposed for control and stabilization of three-dimensional uncertain fractional-order systems. the robust controller is designed on the basis of fractional lyapunov stability theory. furthermore, the effects of model uncertainti...

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems ...