摘要
随着农业大数据发展和计算机技术的不断成熟,人们能够快速准确地获得信息。在大数据背景下,利用传统的时间序列模型对农产品销量进行预测已经不能满足人们的需求,神经网络凭借其强大的非线性映射能力在销量预测领域得到了广泛应用。本文综述了国内外学者应用在农产品销量预测上的主要方法,介绍了神经网络在农产品销量预测领域的应用,客观阐述了神经网络在预测中可能存在的问题,并展望未来农产品销量预测研究发展方向,以期为农产品市场稳定协调发展提供参考。
With the development of agricultural big data and the maturity of computer technology, people can get information quickly and accurately. Under the background of big data, using the traditional time series model to predict the sales of agricultural products can not meet the needs of people. Neural network has been widely used in the field of sales forecast for its strong nonlinear mapping ability. This paper summarized the main methods used by domestic and foreign scholars in the sales forecast of agricultural product, introduced the application of neural network in the field of agricultural product sales forecast,objectively explained the possible problems of neural network in the forecast, and looked forward to the future development direction of agricultural product sales forecast, in order to provide references for the stable and coordinated development of the agricultural product market.
作者
崔云浩
朱军
孟浩
CUI Yunhao;ZHU Jun;MENG Hao(College of Information and Computer Science,Anhui Agriculture University,Hefei Anhui 230036)
出处
《现代农业科技》
2021年第17期262-266,共5页
Modern Agricultural Science and Technology
基金
安徽省科技重大专项(18030701202)
贵州省科技成果应用及产业化计划项目(2021-119)。
关键词
农产品
神经网络
时间序列
销量预测
agricultural product
neural network
time series
sales forecast
