Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be attributed to variations of its input factors. SA is increasingly being used in environmental modelling for a variety of purposes, including uncertainty assessment, model calibration and diagnostic evaluation, dominant control analysis and robust decision-making. In this paper we review the SA lit...

A new evidential fusion architecture is proposed to build an hybrid artificial intelligent system for people surveillance in wide open areas. Authorized people and intruders are identified and localized thanks to the joint employment of cameras and RFID tags. Complex Event Processing and Transferable Belief Model are exploited for handling noisy data and uncertainty propagation. Experimental re...

The selection of uncertainty structures is an important aspect in system identification for robust control. The aim of this paper is to investigate the consequences for multivariable systems. Hereto, first a theoretical analysis is performed that establishes the connection between the associated model set and the robust control criterion. Second, an experimental case study for an automotive app...

iTOUGH2 provides inverse modeling capabilities for the TOUGH2 family of nonisothermal multiphase flow simulators. It can be used for a formalized sensitivity analysis, parameter estimation by automatic model calibration, and uncertainty propagation analyses. While iTOUGH2 has been successfully applied for the estimation of a variety of parameters based on different data types, it is recognized ...

s: In this paper, we propose an algorithm that leverages road markings obtained from monocular camera images to estimate accurate vehicle position. Our method generates sub-maps containing only road markings that increase the confidence of the matching to improve the accuracy of the loop detection. The cumulative error is compensated by the detected loop, thereby increasing the overall global a...

The first paper, by Seneff, Hirschman and Zue, concerned the ATIS domain. The authors state what seems, after it is pointed out, an obvious truth, but which too few system builders seem to understand: when attempting a project like ATIS, the time to worry about the kinds of interaction that will take place in a dialogue is at the very beginning of the project. The MIT ATIS system has not yet be...

The Smith predictor is a type of compensator that eliminates a time-delay occurred in industrial processes. Recently, the robustness in of the Smith predictor has been great issue. In this paper, a robust Smith predictor design is investigated, in this paper, the system identification method is used to find out a nominal model and its uncertainty bound of the nominal model is quantified in the ...

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...

This paper shows an approach to identify the uncertainty of the parameters in a lumped parameter model from experimental data. This approach is applied to a hydrostatic drivetrain setup in which the behavior of both the hydraulic pump and motor vary as the temperature of the oil changes. The model contains a large amount of parameters, describing the dependency between the speed, pressure and s...

A full-scale seven-story reinforced concrete shear wall building structure was tested on the UCSDNEES shake table in the period October 2005–January 2006. The shake table tests were designed so as to damage the building progressively through several historical seismic motions reproduced on the shake table. A sensitivitybased finite element (FE) model updating method was used to identify damage ...