Agricultural product price prediction method and apparatus

Abstract

The invention discloses an agricultural product price prediction method and apparatus, which is applied to the field of information processing. The method comprises the steps of obtaining M price prediction samples of a first type of agricultural product, wherein M is at least one hundred; decomposing the M price prediction samples into k price VM (Variational Mode) components with different vibration frequency features through VMD (Variational Mode Decomposition), and inputting the k price VM components to an SVM prediction model optimized through a firefly algorithm to perform prediction, thereby obtaining k VM component prediction values corresponding to the k price VM components; and linearly superposing the k VM component prediction values to obtain a price prediction value of the first type of agricultural product. Through the method and the apparatus, the price prediction precision of the agricultural product is improved.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a method and device for predicting prices of agricultural products. Background technique [0002] The price of agricultural products directly affects the production and circulation of agricultural products. Scientific forecasting of agricultural product prices has important practical significance for avoiding market risks of agricultural products and promoting agricultural structural adjustment and sustainable development. In recent years, the price of agricultural products in my country has been affected by various factors such as national policies, market supply and demand, production costs, natural climate, and emergencies, showing characteristics such as high noise, non-stationary, and non-linear, which not only leads to the price of my country's soybean industry Risks are increasing and adding to the difficulty of forecasting soybean prices. [0003] At present, the met...

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Problems solved by technology

[0003] At present, the methods for predicting the price of agricultural products include: regression analysis method, time series method, gray prediction method, fuzzy theory method, neural network prediction method, etc., but the above single prediction method is still difficult to obtain satisfactory results for non-stationary and nonlinear time series. forecast result

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