易腐食品安全预警云体系构建研究

Early warning method of fresh chicken preservation period based on SVM

运用支持向量机(Support Vector Machine,SVM)和现代信息技术(含云计算、物联网、大数据等)构建了易腐食品安全预警云体系,并以冷鲜鸡肉保鲜期预警为例,基于模拟云端数据建立MATLAB仿真,得出其有效积温云数据与过氧化云数据之间的关系,并进行回归预测,之后为验证SVM准确性又通过有效积温与过氧化值的组合预测,将结果与实际值对比分析。结果表明:基于现代信息技术的SVM预警模型比以往传统方法能得到更精确的预测结果。

Using support vector machine(SVM vector machine,svm)and modern information technology(including cloud computing,Internet of Things,big data and other technologies)to build a perishable food safety early Warning cloud system.Taking the early warning of cold and fresh chicken preservation period as an example,MATLAB simulation is established based on simulated cloud data,and the relationship between effective accumulated temperature cloud data and peroxide cloud data is obtained,and regression prediction is carried out.Then,in order to verify the accuracy of SVM,and through the combination prediction of effective accumulated temperature and peroxide value,the results are compared and analyzed with the actual values.The results show that the SVM early warning model based on modern information technology can obtain more accurate prediction results than the previous traditional methods.