Nowadays, with the rapid development of science and technology, a number of new technologies have emerged. New scientific fields such as data mining and machine learning have been deeply studied. Many intelligent algorithms have emerged and applied to different fields. This paper constructs a combined model based on BP (Back Propagation) neural network and SVR (Support Vector Regression). Based on the agricultural product price data, the example verification analysis shows that compared with the single prediction model, the BP-SVR-BP prediction model has greatly improved the prediction accuracy. The fitting effect is closer to the real data curve, which can objectively and truly reflect the law of agricultural product price changes.