基于神经网络模型的朝阳市生猪价格预测  

Prediction of hog price in Chaoyang city based on neural network model

作　　者：王艳华[1] WANG Yanhua(Department of Mathematics and Computer,Chaoyang Teachers College,Chaoyang Liaoning 122000)

机构地区：[1]朝阳师范高等专科学校数学计算机系,辽宁朝阳122000

出　　处：《辽宁师专学报（自然科学版）》2024年第1期10-14,共5页Journal of Liaoning Normal College(Natural Science Edition)

基　　金：2019年辽宁省教育厅项目(JYT19L03)。

摘　　要：选取2020年1月至2023年6月朝阳市生猪日价格和猪饲料中豆粕的日价格作为研究数据,分别建立BP神经网络模型和小波神经网络模型对朝阳市生猪价格进行预测.将前160周的价格数据作为BP神经网络模型和小波神经网络模型训练集数据,161~180周的价格数据作为预测数据,通过图形显示预测值和实际值变化,计算2种神经网格模型的平均绝对误差和均方根误差.通过误差比较分析得出,在朝阳市生猪价格波动领域,小波神经网络模型优于BP神经网络模型,建议推广应用.The daily prices of hog and the daily prices of soybean meal in pig feed in Chaoyang city from January 2020to June 2023were selected as the research data,and the BP neural network model and the wavelet neural network model were constructed respectively to predict the price of hog in Chaoyang city.The price data of the first 160weeks were used as the training set data of BP neural network model and wavelet neural network model,the price data of 161to 180weeks were used as the forecast data.The changes of forecast value and actual value were shown by graphs,and the mean absolute error and root mean square error of the two neural grid models were calculated.By analyzing the error comparison,it is concluded that the wavelet neural network model is better than BP neural network model in the field of pig price fluctuation in Chaoyang city,which is recommended to popularize the application.

关 键 词：BP神经网络模型 小波神经网络模型 生猪价格预测 

分 类 号：F323.7[经济管理—产业经济]