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 literature with the goal of providing: (i) a comprehensive view of SA approaches also in relation to other methodologies for model identification and application; (ii) a systematic classification of the most commonly used SA methods; (iii) practical guidelines for the application of SA. The paper aims at delivering an introduction to SA for non-specialis...
Modelling is crucial to understand the behavior of environmental systems.Adeeper comprehension of a ...
As computing power increases and data relating to elementary chemical and physical processes improve...
Abstract. Environmental models often involve complex dynamic and spatial inputs and outputs. This ra...
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be a...
AbstractSensitivity Analysis (SA) investigates how the variation in the output of a numerical model ...
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be a...
This document is a review of sensitivity analysis methods. It aims to contribute to the general unde...
Sensitivity analysis (SA) is a valuable tool to support the use of mathematical models for environme...
Mathematical models are useful tools for studying many problems in the environmental and public heal...
Mathematical models are utilized to approximate various highly complex engineering, physical, enviro...
Uncertainty and sensitivity analysis (UA/SA) aid in assessing whether model complexity is warranted ...
A parametric sensitivity analysis was conducted on a well known model for the production of a key su...
Computer based modelling methods are being used increasingly to replicate natural systems in order t...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
The purpose of this report is to propose a general procedure for sensitivity analysis when used to e...
Modelling is crucial to understand the behavior of environmental systems.Adeeper comprehension of a ...
As computing power increases and data relating to elementary chemical and physical processes improve...
Abstract. Environmental models often involve complex dynamic and spatial inputs and outputs. This ra...
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be a...
AbstractSensitivity Analysis (SA) investigates how the variation in the output of a numerical model ...
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be a...
This document is a review of sensitivity analysis methods. It aims to contribute to the general unde...
Sensitivity analysis (SA) is a valuable tool to support the use of mathematical models for environme...
Mathematical models are useful tools for studying many problems in the environmental and public heal...
Mathematical models are utilized to approximate various highly complex engineering, physical, enviro...
Uncertainty and sensitivity analysis (UA/SA) aid in assessing whether model complexity is warranted ...
A parametric sensitivity analysis was conducted on a well known model for the production of a key su...
Computer based modelling methods are being used increasingly to replicate natural systems in order t...
Existing guidelines for impact assessment recommend that mathematical modelling of real or man-made ...
The purpose of this report is to propose a general procedure for sensitivity analysis when used to e...
Modelling is crucial to understand the behavior of environmental systems.Adeeper comprehension of a ...
As computing power increases and data relating to elementary chemical and physical processes improve...
Abstract. Environmental models often involve complex dynamic and spatial inputs and outputs. This ra...