Model sensitivity analysis demonstrates the importance of incorporating meteorological, hydrological, and geomorphological controls on stream temperature in modelling studies.
Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis.
However, some methods and algorithms were developed to shorten the NDoE process, as sensitivity analysis, surrogate modelling and adaptive DoE.
This paper proposed a renovated passive design assessment system for green building labelling based on robust energy end-use statistics, different global sensitivity analysis methods, modelling experiments and a detailed case study.
In order to reduce the dimensionality of input data and achieve better performance of neural network, dimensionality reduction techniques: Principal Component Analysis, Forward stepwise sensitivity analysis and dimensionless modelling parameter approach were applied.
Reported experience and modelling approaches, such as decision-tree sensitivity analysis, can demonstrate that these management changes translate to improved cost-effectiveness (Fig. 3).
In the modelling study we also perform probabilistic sensitivity analysis to test parameter uncertainty and to construct cost-effectiveness acceptability curves.
Five of the six predictors identified in the modelling process were also present in sensitivity analysis using non-imputed data and dichotomised respiration rate and heart rate variables, again supporting the final model.
Using global variance-based sensitivity analysis, influence of nonlinear modelling approaches on uncertainty propagation is studied.
Impact is determined by a detailed modelling study using both local and global sensitivity analysis methods together with correlation analysis.
