Research On Fruit Price Prediction And Sales Strategy Based On Big Data Mining

Fruit industry is an important industry in our country,has an important role in national economic life,how to make fruit industry healthy development has the very big practical significance,from the perspective of forecast fruit price trend of development to provide guidance for the development of fruit industry also becomes very important,need more experts and scholars in this area to provide intellectual support.Based on the development of fruit industry,this thesis takes the apple industry as an example to discuss the prediction of apple price trend that maximizes the relative income of fruit farmers and the sales strategy.The main work of this thesis includes:1.The apple price determination system is regarded as a gray system,and the gray GM(1,1)model is used to predict the apple price.At the same time,the average price forecast of the three months from December to February of the next year is mainly considered from the optimal sales strategy of fruit farmers,and the corresponding prediction results are obtained.2.Consider the apple price changes with its regularity,its future price changes affected by the price of the past and present,can will apple price history data as a time series,using the nonlinear regression analysis of the time series analysis method(NAR)to process the evaluation price forecast is right,because of considering the nonlinear processing difficulties,The neural network has great advantages in solving nonlinear problems,so the NAR neural network composed of NAR model combined with neural network model is finally considered to predict the apple price.3.The grey GM(1,1)model and the NAR neural network model predict apple prices separately.Both models have certain advantages in predicting apple prices,but as a single prediction model,they also have their own shortcomings.In order to give full play to the respective advantages of grey GM(1,1)model prediction and NAR neural network model,it is more likely to improve the accuracy and accuracy of the prediction system by combining them.4.By investigating the yield and planting area of apples at home and abroad,analyze the influence of the apple industry in planting,storage,circulation and sales on the price,and obtain the main influencing factors on the selling price of fruit farmers.In order to stabilize the income of fruit farmers and discuss the sales strategy of fruit farmers,The analytic hierarchy process(AHP)method is adopted to solve the decision problem that the target value is difficult to describe quantitatively by fuzzy quantification of qualitative indexes,and the optimization strategy of fruit farmers selling apples is given according to the quantitative analysis results.In this thesis,the grey GM(1,1)model and NAR neural network are used to predict the apple price separately or in combination,and some results are obtained.There are many kinds of prediction models.For fruit price prediction,whether there is a better single prediction model and its combination prediction can be used needs further research and practice.