Agricultural product price prediction method, storage medium and computing device
A technology for price forecasting and agricultural products, applied in market forecasting, neural learning methods, biological neural network models, etc., can solve problems such as low accuracy and long time-consuming price forecasting, and achieve long time-consuming, time-saving, and improved computing the effect of time
Pending Publication Date: 2021-03-05
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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[0004] The technical problem to be solved by the present invention is to provide a method for predicting the price of agricultural products, a storage medium and a computing device to solve the problems of long time-consuming and low accuracy in predicting the price of agricultural products.
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[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0050]It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.
[0051] It should also be understood that the terminology used i...
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The invention discloses an agricultural product price prediction method, a storage medium and computing equipment, and the method comprises the steps: collecting agricultural product price impact factors, carrying out the preprocessing of daily price data in a historical price data set N, and selecting training data and comparison data; selecting an existing seq2seq model based on the CNN to obtain a trained seq2seq model; selecting an existing LSTM model to obtain a trained LSTM model; selecting an agricultural product to be predicted, processing the original historical price data of the agricultural product to be predicted into multi-dimensional index data, and inputting the multi-dimensional index data into the trained seq2seq model to obtain a prediction result Cs; and inputting the training data into the trained LSTM model to obtain a quasi-prediction result Cr, and correcting the quasi-prediction result Cr to obtain a final prediction price C of the agricultural product to be predicted. According to the invention, the problems of long time consumption and low accuracy of agricultural product price prediction can be solved.
Description
technical field [0001] The invention belongs to the technical field of price forecasting, and in particular relates to a price forecasting method for agricultural products, a storage medium and a computing device. Background technique [0002] There are many factors that affect the price fluctuations of agricultural products, such as seasonal factors, temperature and humidity factors, supply and demand of agricultural products in different seasons, per capita consumption, and macro and micro regulation of the market economy. This has led to the prediction of agricultural product prices. difficult. [0003] However, none of the state-of-the-art models closely fit actual price changes. The influence of controllable and uncontrollable factors leads to low prediction accuracy of existing models, and the prediction of agricultural product prices takes a long time and has low accuracy. Contents of the invention [0004] The technical problem to be solved by the present inventi...
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IPC IPC(8): G06Q30/02G06N3/04G06N3/08
CPCG06Q30/0206G06N3/049G06N3/08G06N3/045
Inventor 边根庆张轶翔
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY