Risk assessment is an important and significant aid in the decision making process. Risk assessment is performed using ‘model’ and a model is a function of parameters which are usually affected by uncertainty. Some model parameters are affected by aleatory uncertainty and some others are affected by epistemic uncertainty. In this paper we propose a hybrid method to deal with propagation of both...

Analytical investigations of real-world, hybrid dynamical systems are technically challenging. Consequently, simulation plays a vital role in their analysis. Simulation typically addresses forward problems though, offering limited insights into parametric influences. The paper addresses this issue, presenting computationally efficient algorithms that extend the capabilities of simulation. The s...

Software projects are required to be tracked during their execution for controlling them. According to state space approach, the tracking problem leads us to have a project state transition model and project status model. A key factor in modeling software projects is to model the project with uncertainty involved in the parameters related to project state transition model and project status mod...

In this article, the authors present a hybrid approach to produce more accurate land cover maps of diverse landscapes representing Mediterranean environments. The innovation of the proposed methodology is to use, in the combination of soft classifiers outputs, information about the classification uncertainty associated with each pixel and its neighbourhood. The hybrid combined classification me...

1. Abstract The purpose of this article is to present a Chance Constrained Optimization of an unconventional configuration of hybrid-powered-aircraft. The Chance Constrained Methodology is applied using a method of uncertainty propagation based on error distribution moments. The hybrid configuration is compared to a conventional, pure thermodynamic one, both being designed according to the same...

The major problems facing the decision making is how to handle uncertain data, several theories are dealing with uncertainty, soft set theory also handle this uncertainty problem. Reduction techniques are still an open area to be explored in knowledge management, which focuses on uncertain data removing unlike comparisons. This paper proposes based on rough set theory and soft set theory, it de...

In this paper we present an algorithm for the design of robust model-based predictive control for hybrid system under uncertainty via parametric programming. The proposed min-max hybrid control scheme guarantees feasible plant operation for the maximum violation of uncertainty scenario. The key advantage of the proposed hybrid controller design is reduction in expensive, repetitive in nature on...

A robust hybrid control strategy for a broad class of hybrid nonlinear processes with actuator constraints and uncertain dynamics is proposed. These ®ariable-structure processes comprise a finite family of constrained uncertain continuous nonlinear dynamical subsystems, together with discrete e®ents that trigger the transition between the continuous subsystems. The proposed control strategy is ...

The use of a hybrid approach classification, which combines pixels and objects, has been shown to be suitable for the identification of Landscape Units that contain a variety of land cover objects using VHSR images. However, the pixel-based classification of remote sensing images performed with different classifiers usually produces different results. With the combination of the outputs of a se...