基于机器学习的食品安全风险预警研究现状与展望

Current Status and Prospect of the Study on Food Safety Risk Early Warning on the Basis of Machine Learning

介绍机器学习基本思想、分类与常用方法以及发展历史,阐述机器学习在食品安全风险预警方面应用现状,包括BP神经网络、贝叶斯网络、自回归求和移动平均模型及决策树方法、支持向量机模型等,分析当前发展中存在的问题并讨论未来发展方向。

The paper introduces the basic idea,classification,common method and development history of machine learning,elaborates on the application status of machine learning in food safety risk early warning,including BP neural network,Bayesian network,Autoregressive Integrated Moving Average(ARIMA)model and Decision Trees(DT),Support Vector machines(SVM)model,etc.It also analyzes the current issues in the development and discusses the future direction.