基于LSTM模型的小麦价格预测研究  

Research on Wheat Price Prediction Based on LSTM Modeling

作　　者：常广明 赵霞[1] CHANG Guangming;ZHAO Xia(School of Information Science and Technology,Gansu Agricultural University,Lanzhou Gansu 730070)

机构地区：[1]甘肃农业大学信息科学技术学院,甘肃兰州730070

出　　处：《软件》2024年第11期42-45,共4页Software

摘　　要：小麦作为基础消费品,其价格直接关系到人民的生活水平,也是政府机构对小麦生产调控的重要依据。受到生产成本、市场因素、自然灾害等影响,小麦价格具有波动性、非线性的特点。现有对于波动性变化比较大而且具有非线性的小麦价格预测方法单一,表现不理想。因此,本文采用了长短期记忆神经网络(LSTM)模型对小麦价格进行研究,该模型适用于分析历史价格变化情况,获取价格的周期性变化规律。本文主要从小麦收购价与小麦收购量之间的关系进行研究,从而预测小麦价格的走势。Wheat,as a basic consumer good,has its price directly linked to people's living standards,and it also serves as a crucial basis for government agencies to regulate wheat production.Affected by production costs,market factors,natural disasters,etc.,wheat prices exhibit volatility and nonlinearity.Currently,the methods for predicting wheat prices,which are highly volatile and nonlinear,are limited and perform unsatisfactorily.Therefore,this paper employs a Long Short-Term Memory(LSTM)model to study wheat prices.This model is suitable for analyzing historical price changes and obtaining the cyclical patterns of prices.This paper primarily investigates the relationship between wheat purchase prices and wheat purchase volumes,aiming to predict the trend of wheat prices.

关 键 词：小麦 LSTM模型 价格预测 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] S512.11[自动化与计算机技术—控制科学与工程]