关键词: 生鲜乳价格, 预警, BP神经网络, 季节调整法, Holt双参数指数平滑法

Abstract: In order to stabilize the price of fresh milk and ensure the supply of fresh milk, combined with the characteristics of modern urban agriculture, taking Tianjin as an example, prewarning mechanisms for monthly and annual price fluctuations of fresh milk were constructed. Monthly prices were predicted based on seasonal adjustment method and Holt double parameter exponential smoothing method, and a prewarning mechanism of annual price fluctuation of fresh milk was established based on BP neural network model. The results showed that combined forecast of monthly price was ideal, the price of fresh milk from January to June in 2022 would be maintained at about 4.34-4.38 yuan/kg, the price fluctuation of fresh milk were seasonal, and the price fluctuation of fresh milk at the end of each year was prone to positive light alarm or even positive heavy alarm. BP neural network model had a high prediction accuracy for annual price fluctuation of fresh milk. The test result in 2019 was 0.101 5, which was close to the actual value of 0.106 7 in 2019 and showed no alarm state. This model could be used to warn annual price fluctuation of fresh milk. In order to stabilize the price of fresh milk, we should establish a scientific and effective market information collection, analysis and release mechanism, strengthen the prewarning and monitoring of fresh milk price fluctuation, establish and optimize the price negotiation mechanism of fresh milk.

Key words: fresh milk price, prewarning, BP neural network, seasonal adjustment method, Holt double parameter exponential smoothing method