Nonlinear model validation using correlation tests

Nonlinear Model Validation using Multiple Experiments

Model validation is the formulation of an experiment to test the predictive power of a candidate model. This paper considers an atypical method for combining multiple experiments, which arises due to our choice of measure. We explore a framework for combining multiple experiment information using bifurcation theory. We follow the approach of successive deduction, hypothesis formulation and fals...

Using Correlation in MFM Model Design and Validation

Industrial process signals do affect one other. However, causal dependencies, or correlation, and thereby consequences of control actions cannot always be understood by the operator, which may lead to accidents. Models explain dependencies and are mostly built on process knowledge and blueprints, while causalities are visible in the measurements and ought to be used to increase process understa...

A set of novel correlation tests for nonlinear system variables

A set of novel correlation tests using omni-directional cross-correlation functions (ODCCFs), which are based on the first order cross-correlation functions (CCF), are proposed in the present study to comprehensively detect nonlinear relationships between variables. Then the ODCCFs are combined into a set of concise formulations to provide better illustration of detected correlations and reduce...

Model Based vs. Model Independent Tests for Cross-Correlation

Barrier certificates for nonlinear model validation