Modelling of dynamic cerebral pressure autoregulation using sequential genetic algorithm (Q614197)

Summary: Accurate modelling is desirable for analysis and clinical studies of physiological systems. The present work provides methodology for fully automated sequential genetic algorithm (SGA) for autoregressive exogenous (ARX) modelling. The SGA has been implemented to determine the proper model structure and thereafter the model parameters. The proposed algorithm has been tested on known ARX models and sunspot data modelling problems. Finally, SGA has been applied to model the dynamic cerebral autoregulation (CA) system. The results are promising and models obtained using SGA are better as compared to standard least square (LS) algorithms and can be reliably applied to model physiological system.