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Agricultural Product Price Forecasting Methods: A Review

Journal

AGRICULTURE-BASEL
Volume 13, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/agriculture13091671

Keywords

price forecasting; combined models; intelligent prediction methods; agricultural product price

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This article discusses the research methods and challenges in agricultural price prediction and identifies future trends, including using combination models for prediction, integrating different types of data for improved accuracy and precision. It is hoped that this article will provide assistance in the development of research in this field.
Agricultural price prediction is a hot research topic in the field of agriculture, and accurate prediction of agricultural prices is crucial to realize the sustainable and healthy development of agriculture. It explores traditional forecasting methods, intelligent forecasting methods, and combination model forecasting methods, and discusses the challenges faced in the current research landscape of agricultural commodity price prediction. The results of the study show that: (1) The use of combined models for agricultural product price forecasting is a future development trend, and exploring the combination principle of the models is a key to realize accurate forecasting; (2) the integration of the combination of structured data and unstructured variable data into the models for price forecasting is a future development trend; and (3) in the prediction of agricultural product prices, both the accuracy of the values and the precision of the trends should be ensured. This paper reviews and analyzes the methods of agricultural product price prediction and expects to provide some help for the development of research in this field.

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