The quality of measurements depends directly on the quality of the measurement system model. With this concern, novel hybrid modelling techniques have been formulated for model performance enhancement. Air-gauge focus system sensor modelling has been accomplished by theoretical and empirical data integration. These modelling techniques combine a priori knowledge in theoretical model elaboration, and to attain the enhanced levels of adequacy, accuracy and precision they approximate the exact unknown model, simultaneously by available theoretical and appropriate polynomial empirical functions. For such a hybrid model the solution of two approaches by means of linear transformation and successive linear and nonlinear transformations have been developed. The validations of elaborated air-gauge sensor models revealed that sensor hybrid model solving by successive linear and nonlinear transformations permits us to attain minimum discrepancy with empirical evidence for the whole region of interest for model predictor variables.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.