Research On Prediction Of Dairy Products Quality Based On Neural Network

Nowadays food quality and safety is the most concern of the people. With the growth of Chinese economic, the increase in national income and the continuously improve in people’s life quality, dairy products have become one of the essential food in people’s life. Its quality not only affects the reputation of manufacturing company, but also affects people’s health. Therefore, the study of the computer technology using in product quality prediction can effectively control the product quality and also can reduce the workload of Quality Supervision and Inspection. Meanwhile, it is of great significance for ensuring dairy quality. Using advanced artificial intelligence in the process of dairy production to control quality intelligently is the trend of development in the quality management of today’s dairy companies.Due to the wide variety of dairy kinds and the complexity of the production process as well as every aspect of production control may become the key factor affecting the final product quality, this paper made a simulation of dairy quality prediction with the popular neural network technology and realized it in the system. The main work is as follows:1. Based on the deep study of the dairy production process, the paper analyzed the systematic requirements of the dairy quality prediction software in detail, proposed solution of the quality prediction system for dairy products and made a modular design to a dairy forecasting system.2. Due to the characteristics of artificial neural network, such as self- adaptive, self-organizing and self-learning ability, according to the dairy production characteristics, this paper built a dairy quality prediction model based on artificial neural networks, which has laid a theoretical foundation for a deep study of the topic.3. This paper used the normalization method to process the sample data in order to reduce the influence to the neural network model training. It made simulations separately using the quality prediction models of the BP neural network and RBF neural network by means of MATLAB software. The experimental data shows that RBF neural network model could be used in quality prediction system.4. This paper made analysis, design and Implementation to the system database by means of new SSH framework. That is to say, using Hibernate as the persistence layer, struts as the presentation layer spring as service layer and combined with framework integrated approach, this paper realized some functions of the B / S modeled dairy quality prediction system. The result shows that the method using in dairy quality prediction system is feasible and effective.