摘要
为了对食用菌电子商务销量进行准确预测,设计了基于深度学习的预测模型。在对食用菌销量数据进行预处理的基础上,采用卷积神经网络建立了销量预测训练模型。通过100个样本训练集的输入,可以达到99%的准确率,能够满足食用菌销量预测模型的精度要求。
In order to accurately predict the sales volume of e-commerce of edible fungi,a prediction model based on deep learning was designed.On the basis of preprocessing the data of sales volume of edible fungi,the training model of sales volume prediction was established by convolution neural network.Through the input of 100 sample training sets,the accuracy of 99%can be achieved,which can meet the accuracy requirements of the sales forecast model of edible fungi.
作者
胡玲
HU Ling(Department of Economic Management,Hetao College,Bayannaoer 015000,China)
出处
《中国食用菌》
北大核心
2020年第3期162-164,共3页
Edible Fungi of China
基金
河套学院科学技术研究项目(HYSQ201735)。
关键词
食用菌
销量预测模型
深度学习
数据预处理
卷积神经网络
edible fungi
sales volume prediction model
deep learning
data preprocessing
convolutional neural network
