As models are simplifications of reality, the management of the uncertainty arising along the whole modelling process is a crucial and delicate operation, which primarily affects the credibility of model results. In the field of traffic simulation to tackle this issue, it is common practice to include the model uncertainty alongside the uncertainty in the parametric inputs. However, reducing the uncertainty in the modelling process through the indirect estimation of the model parameters is far from being simple. In this picture, a key role can be played by model sensitivity analysis. In the present work, in particular, the role of sensitivity analysis in the management of modelling uncertainties is firstly illustrated. Then, one of the most...
This paper examines a metamodel-based technique for model sensitivity analysis and applies it to the...
This paper discusses a metamodel-based technique for model sensitivity analysis and applies it to th...
As modeling and simulation becomes a more important part of the modeling process, the demand on a kn...
As models are simplifications of reality, the management of the uncertainty arising along the whole ...
In this paper, a multi-step sensitivity analysis approach for model calibration is proposed and appl...
In this work variance-based techniques for model sensitivity analysis have been discussed and applie...
In recent time, in the field of traffic simulation, sensitivity analysis (SA) is starting to attract...
In this work variance-based techniques for model sensitivity analysis have been discussed and applie...
A single source of information for researchers and professionals, Traffic Simulation and Data: Valid...
The reliability of traffic model results is strictly connected to the quality of its calibration. A ...
With the increasing level of detail of traffic simulation models, the need for a consistent understa...
Quantitative sensitivity analysis (QSA) of models is becoming an essential element of model-based an...
This paper examines a metamodel-based technique for model sensitivity analysis and applies it to the...
Automated calibration of microscopic traffic flow models is all but simple for a number of reasons, ...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
This paper examines a metamodel-based technique for model sensitivity analysis and applies it to the...
This paper discusses a metamodel-based technique for model sensitivity analysis and applies it to th...
As modeling and simulation becomes a more important part of the modeling process, the demand on a kn...
As models are simplifications of reality, the management of the uncertainty arising along the whole ...
In this paper, a multi-step sensitivity analysis approach for model calibration is proposed and appl...
In this work variance-based techniques for model sensitivity analysis have been discussed and applie...
In recent time, in the field of traffic simulation, sensitivity analysis (SA) is starting to attract...
In this work variance-based techniques for model sensitivity analysis have been discussed and applie...
A single source of information for researchers and professionals, Traffic Simulation and Data: Valid...
The reliability of traffic model results is strictly connected to the quality of its calibration. A ...
With the increasing level of detail of traffic simulation models, the need for a consistent understa...
Quantitative sensitivity analysis (QSA) of models is becoming an essential element of model-based an...
This paper examines a metamodel-based technique for model sensitivity analysis and applies it to the...
Automated calibration of microscopic traffic flow models is all but simple for a number of reasons, ...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
This paper examines a metamodel-based technique for model sensitivity analysis and applies it to the...
This paper discusses a metamodel-based technique for model sensitivity analysis and applies it to th...
As modeling and simulation becomes a more important part of the modeling process, the demand on a kn...