This study is aimed at the development of a model for an experimental vapour-phase fungi bioreactor, which could be derived in a simple way using the available measurements of a pilot-plant reactor, without the development of ad hoc experiments for the evaluation of fungi kinetics and the estimation of parameters related to biofilm characteristics. The proposed approach is based on hybrid models, obtained by the connection of the mass balance equation (used in traditional phenomenological models) with a feedforward neural network (used in black-box modelling), and the proper use of statistical tools for the model assessment and system understanding. Two different hybrid models were developed and compared by proper performance indexes, and their capability to predict the biological complex phenomena was demonstrated and compared to that of a first-principle model.
Spigno, G., Tronci, S., Development of hybrid models for a vapor-phase fungi bioreactor, <<MATHEMATICAL PROBLEMS IN ENGINEERING>>, 2015; 2015 (N/A): N/A-N/A. [doi:10.1155/2015/801213] [http://hdl.handle.net/10807/70009]
Development of hybrid models for a vapor-phase fungi bioreactor
Spigno, Giorgia;
2015
Abstract
This study is aimed at the development of a model for an experimental vapour-phase fungi bioreactor, which could be derived in a simple way using the available measurements of a pilot-plant reactor, without the development of ad hoc experiments for the evaluation of fungi kinetics and the estimation of parameters related to biofilm characteristics. The proposed approach is based on hybrid models, obtained by the connection of the mass balance equation (used in traditional phenomenological models) with a feedforward neural network (used in black-box modelling), and the proper use of statistical tools for the model assessment and system understanding. Two different hybrid models were developed and compared by proper performance indexes, and their capability to predict the biological complex phenomena was demonstrated and compared to that of a first-principle model.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.