基于大数据挖掘的医院食品安全风险预测管理模型

Risk prediction management model of hospital food safety based on big data mining

目的设计基于大数据挖掘的医院食品安全风险预测管理模型。方法建立医院食品安全风险评估指标体系,并采用三标度法比较影响食品安全指标的重要程度,得到各个指标的权重,后计算食品样品中检测指标不合格率与不合格数,将检测指标的不合格率与不合格数结合为一个风险系数,完成对医院食品安全风险预测。结果实验证明,此次设计的基于大数据挖掘的医院食品安全风险预测管理模型比传统模型预测准确度高。结论可为食品安全领域的发展提供参考依据。

Objective To design a risk prediction management model of hospital food safety based on big data mining.Methods The index system of hospital food safety risk assessment was established.The three-scale method was used to compare the importance of influencing food safety indexes,and the weight of each index was obtained.After that,the unqualified rate and unqualified number of detection indexes in food samples were calculated,and the unqualified rate and unqualified number of detection indexes were combined into a risk coefficient to complete the risk prediction of hospital food safety.Results The experiment proves that the hospital food safety risk prediction and management model designed based on big data mining is more accurate than the traditional model.Conclusion It can provide reference for the development of food safety field.