Modeling And Optimization Of Food Freeze Process

Food processed with freezing has been widely applied in natural life. However, the process of the food frozen is a complex daynamic process which includes the bromatology, diathermancy, polymer and other related topics. Consequently making a research on the process the food frozen and elstablishing and optimizing the food frozen system under very complex conditions have a significant influence on the optimization of freezing food arts, the decreases of energy consumption in freezing process, and the improvement of freezing equipments.In this paper, we addressed the problem of the modeling of the freezing process of food. Based on the feed forward neural network theory, we model ans simulate the freezing process of food. The main work done include: 1. Making a research on the physical model and frozen mechanism of several kinds of food. 2. Under certain assumption, we establish the non-static mathematical model of the process of food freezing, the analysis solution of the model and the finite difference method are analyzed. 3. A gentic algorithm based radical basis function neural network is proposed to approximate and predict the characteristic of food frozen process model. Some simulations are made and the results shown that the GA-RBF neural network can remarkably improve the searching efficiency in the training and accuracy of predicting, thus can replace some available mathematical models to model the process of food freezing.The dynamic GA-RBF neural network model propsed in this paper can accurately simulate the process of food frezzing. Moreover, it is a general model and can be used for many kinds of food. The model will have cetain guide guiding significance and practical value.