Analysis of the development strategy of Chinese fruits and vegetables based on neural network and grey prediction

Fruits and vegetables are an important source of nutrients human body needs. In order to scientifically improve nutrition health status of residents in our country, we need to research and plan scientifically the consumption of fruits and vegetables. For purpose of simplifying the research object, we take cluster analysis on the common species of fruits and vegetables based on their nutrients' composition and content, and screen out the fruits and vegetables varieties which account for 90% of the total production. In order to better predict the development trend of the consumption of fruits and vegetables, we use the grey prediction and Back Propagation (BP) neural network to establish mathematical model to estimate the consumption of major fruits and vegetables, and study their development trend. Based on the development trend of fruits and vegetables and the similarity of the function of fruits and vegetables, the linear programming model of individual consumption of fruits and vegetables for our residents is established in a balanced condition. We can achieve optimum cost through the substitution between fruits and vegetables. According to the actual situations, we obtain the feasible optimal solutions and provide reasonable individual consumption of fruits and vegetables for our residents after many times variable substitution.