Agricultural Product Price Forecasting Methods: A Review

Author:

Sun Feihu123,Meng Xianyong123,Zhang Yan123,Wang Yan123,Jiang Hongtao123,Liu Pingzeng123

Affiliation:

1. School of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China

2. Key Laboratory of Huang-Huai-Hai Smart Agricultural Technology, Ministry of Agriculture and Rural Affairs, Taian 271018, China

3. Agricultural Big-Data Research Center, Shandong Agricultural University, Taian 271018, China

Abstract

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.

Funder

Major Agricultural Applied Technology Innovation Project of Shandong Province

Key Research Development Program (Major Science and Technology Innovation Projects) of Shandong Province

Major Science and Technology Innovation Project of Shandong Province

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

Reference69 articles.

1. Zheng, L. (2013). Model Construction and Empirical Study on Production and Consumption Forecasting of Major Agricultural Products in China. [Master’s Thesis, University of Chinese Academy of Sciences].

2. Cao, Y.L., and Mohiuddin, M. (2019). Sustainable Emerging Country Agro-Food Supply Chains: Fresh Vegetable Price Formation Mechanisms in Rural China. Sustainability, 11.

3. Forecasting Chinese domestic soybean price based on Q-RBF neural network model;Zhang;Soybean Sci.,2017

4. Tothova, M. (2011). Methods to Analyse Agricultural Commodity Price Volatility, Springer.

5. The price characteristics, problems and solutions of vegetables in China;Xiao;Res. Agric. Mod.,2016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3