NARX Neural Network Modelling of Mushroom Dynamic Vapour Sorption Kinetics

作     者：Argyropoulos, Dimitrios Paraforos, Dimitris S. Alex, Rainer Griepentrog, Hans W. Müller, Joachim 

作者机构：University of Hohenheim Institute of Agricultural Engineering 440e Garbenstr. 9 StuttgartD-70599 Germany University of Hohenheim Institute of Agricultural Engineering 440c Garbenstr. 9 StuttgartD-70599 Germany Reutlingen University Process Analysis and Technology Alteburgstr. 150 ReutlingenD-72762 Germany 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2016年第49卷第16期

页      面：305-310页

核心收录：

主　　题：Digital storage Agricultural products Control engineering Fungi Kinetics Moisture control Moisture determination Optimization Sorption Statistical tests Dynamic vapour sorptions Equilibrium moisture contents gravimetric NARX neural network Non linear autoregressive with exogenous Optimization and control Relative humidity and temperatures Sorption isotherms 

摘      要：This paper is concerned with the study, optimization and control of the moisture sorption kinetics of agricultural products at temperatures typically found in processing and storage. A nonlinear autoregressive with exogenous inputs (NARX) neural network was developed to predict moisture sorption kinetics and consequently equilibrium moisture contents of shiitake mushrooms (Lentinula edodes (Berk.) Pegler) over a wide range of relative humidity and different temperatures. Sorption kinetic data of mushroom caps was separately generated using a continuous, gravimetric dynamic vapour sorption analyser at temperatures of 25-40 °C over a stepwise variation of relative humidity ranging from 0 to 85%. The predictive power of the neural network was based on physical data, namely relative humidity and temperature. The model was fed with a total of 4500 data points by dividing them into three subsets, namely, 70% of the data was used for training, 15% of the data for testing and 15% of the data for validation, randomly selected from the whole dataset. The NARX neural network was capable of precisely simulating equilibrium moisture contents of mushrooms derived from the dynamic vapour sorption kinetic data throughout the entire range of relative humidity. © 2016