Over-parameterized models - a complex systems can have simpler models if possible to measure their effect on the state or output. Multi-agent systems - there are local dynamics coupled by a network and identifying nodes with the most impact is cumbersome. Worst-case effect - proposed solution should look at bad trajectories
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tre...
Sensitivities are shown to play a key role in a highly efficient algorithm, presented in this paper,...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
The problem of deciding which inputs in a model influence the most the state or output is often of p...
In this paper time-domain models for sensitivity analysis of linear systems have been developed. The...
Existing methodologies of sensitivity analysis may be insufficient for a proper analysis of Agent-ba...
Methodologies for sensitivity analysis are considered to be of great importance for analyzing agent-...
JSME International Journal, Series C: Dynamics, Control, Robotics, Design and Menufacturing362209-21...
Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part...
A literature review of the use of sensitivity analyses in modelling nonlinear, ill-defined systems, ...
Many human and natural systems are highly complex, because they consist of many interacting parts. S...
Abstract Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. ...
Control of multistable dynamical system has important applications, from physics to biology. Here, w...
The solution of several operations research problems requires the creation of a quantitative model. ...
Mathematical models for signaling pathways are helpful for understanding molecular mechanism in the ...
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tre...
Sensitivities are shown to play a key role in a highly efficient algorithm, presented in this paper,...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
The problem of deciding which inputs in a model influence the most the state or output is often of p...
In this paper time-domain models for sensitivity analysis of linear systems have been developed. The...
Existing methodologies of sensitivity analysis may be insufficient for a proper analysis of Agent-ba...
Methodologies for sensitivity analysis are considered to be of great importance for analyzing agent-...
JSME International Journal, Series C: Dynamics, Control, Robotics, Design and Menufacturing362209-21...
Designing, implementing, and applying agent-based models (ABMs) requires a structured approach, part...
A literature review of the use of sensitivity analyses in modelling nonlinear, ill-defined systems, ...
Many human and natural systems are highly complex, because they consist of many interacting parts. S...
Abstract Sensitivity analysis is an essential paradigm in Earth and Environmental Systems modeling. ...
Control of multistable dynamical system has important applications, from physics to biology. Here, w...
The solution of several operations research problems requires the creation of a quantitative model. ...
Mathematical models for signaling pathways are helpful for understanding molecular mechanism in the ...
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tre...
Sensitivities are shown to play a key role in a highly efficient algorithm, presented in this paper,...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...