Modeling has been used to characterize and map natural hazards and hazard susceptibility for decades. Uncertainties are pervasive in natural hazards analysis, including a limited ability to predict where and when extreme events will occur, with what consequences, and driven by what contributing factors. Modeling efforts are challenged by the intrinsic variability of natural and human systems, m...

The operation planning problem encounters several uncertainties in terms of the power system’s parameters such as load, operating reserve and wind power generation. The modeling of those uncertainties is an important issue in power system operation. The system operators can implement different approaches to manage these uncertainties such as stochastic and fuzzy methods. In this paper, new ...

This paper addresses the problem of checking the consistency of experimental closed-loop frequency-domain data with uncertainty models that are structured using coprime factorizations. The uncertainty models presented in this paper use the knowledge of a stabilizing feedback controller to structure and formulate the uncertainty on a model. Subsequently, the controller dependent coprime factor u...

In modeling and simulation (M&S), we seek to predict the state of a system using a computer-based simulation of a differential equation-based model. In general, the inputs to the model may contain uncertainty due to inherent randomness (aleatory uncertainty), a lack of knowledge (epistemic uncertainty), or a combination of the two. In many practical cases, there is so little knowledge of a mode...

Uncertainty theory is a branch of mathematics for modeling human uncertainty. This paper will answer the following questions: What is uncertainty? In what situations does uncertainty arise? What is the difference between uncertain variable and uncertain set? This paper will also discuss the relations and differences among uncertainty, fuzziness and probability. c ⃝2012 World Academic Press, UK....

In this paper we describe methods applicable to the modeling and control of mechanical manipulation problems, including those that experience uncertain stick/slip phenomena. Manipulation in unstructured environments often includes uncertainty arising from various environmental factors and intrinsic modeling uncertainty. This reality leads to the need for algorithms that are not sensitive to unc...

The fuzzy logic concept provides a natural way of dealing with problems in which the source of imprecision is an absence of sharply defined criteria rather than the presence of random variables. The fuzzy approach considers cases where uncertainties play a role in the control mechanism of the concerned phenomena. Fuzzy modeling includes fuzzification, fuzzy analysis and defuzzification. In this...

-Many models are required for undertaking research into physical phenomena using sensor networks: the source characteristics, the propagation medium, the noise and interference, the sensor transducer and its coupling to the media and the communications among the sensor nodes. Moreover, models are also used for various levels of signal processing and networking abstractions. The entire chain fro...

background: this study aimed at estimating the proportion of diabetes as a risk factor to the attributable burden of cardiovascular diseases in iran. methods: comparative risk assessment methodology was used to calculating potential impact fraction (pif). to calculate pif, data on the prevalence of newly diagnosed diabetes mellitus (ndm) and known diabetes mellitus (kdm) were obtained from 3rd ...