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计算机技术21年10期

基于 BP 神经网络模型的饮食方案研究
崔硕硕,潘霞,邹杰明,朱娜,黄贤英
(桂林电子科技大学 数学与计算科学学院,广西 桂林 541004)

摘  要:为推崇健康饮食,满足各类人群的健康饮食需求,文章提出一个基于 BP 神经网络模型的饮食方案。不同人群对食品的需求千差万别,该文旨在为满足不同人群的多样化需求而为店家提供各式各样的餐饮搭配方案。文章采用 BP 神经网络模型,对前期问卷所收集的桂林周边饮食需求偏好的数据进行分析,得出了各类人群的乐享健康饮食方案。结果表明,BP 神经网络模型在餐饮方面具有较强的适用性。


关键词:健康饮食;营养餐;BP 神经网络模型



DOI:10.19850/j.cnki.2096-4706.2021.10.022


基金项目:2020 年广西大学生创业训练项目 (202010595309)


中图分类号:TP183                                        文献标识码:A                                  文章编号:2096-4706(2021)10-0087-03


Study on Diet Scheme Based on BP Neural Network Model

CUI Shuoshuo,PAN Xia,ZOU Jieming,ZHU Na,HUANG Xianying

(School of Mathematics & Computing Science,Guilin University of Electronic Technology,Guilin 541004,China)

Abstract:In order to advocate healthy diet and meet the healthy diet needs of all kinds of people,this paper proposes a diet scheme based on BP neural network model. As the demand for food varies greatly among different groups of people,this paper aims to provide various catering matching schemes for stores to meet the diversified needs of different people. Using BP neural network model,this paper analyzes the data of dietary demand preference around Guilin collected in the previous questionnaire,and obtains the happy and healthy diet scheme of all kinds of people. The results show that the BP neural network model has strong applicability in the catering aspect.

Keywords:healthy diet;nutritious meal;BP neural network model


参考文献:

[1] 宫国军,罗丽莎 . 餐饮产品开发与营养搭配探析 [J]. 现代 交际,2014(4):108.

[2] 孙婷,李鹏,李一 . 健康家电标准体系的构建 [J]. 家电科 技,2021(3):28-32.

[3] LIU W J,NIU X J,YANG N,et al. Prediction Model of Concrete Initial Setting Time Based on Stepwise Regression Analysis [J]. Materials(Basel,Switzerland),2021,14(12):3201.

[4] 游士兵,严研 . 逐步回归分析法及其应用 [J]. 统计与决策, 2017(14):31-35.

[5] 李友坤 .BP 神经网络的研究分析及改进应用 [D]. 淮南: 安徽理工大学,2012.

[6] CHENG P P,CHEN D L,WANG J P. Research on underwear pressure prediction based on improved GA-BP algorithm [J].International Journal of Clothing Science and Technology,2021,33(4):619-642.


作者简介:崔硕硕(2002—),男,汉族,河南商丘人,本科 在读,研究方向:信息与计算科学。