基于食品类别的消费者食品安全风险感知状态的分类方法研究

Classification Method of Consumer Food Safety Risk Perception Based on Food Categories

消费者食品安全风险感知是主观感知,其感知结果会与客观风险产生偏差,从而造成不必要的恐慌。因此,针对消费者的风险感知主观状态进行分析,提出了三种感知状态,并运用问卷调查实证研究方法,对不同类别的食品消费者风险感知状态进行了解,然后运用神经网络方法,建立了神经网络分类器,其分类准率极高。这表明,在今后的工作中可以利用该分类器对消费者食品安全风险感知状态进行分类,以便采取切实有效的措施。

Consumer food safety risk perception has the characteristic of subjective perception,the perception of results will produce deviation and objective risk,which will cause unnecessary panic.The study analyzed the consumer＇s subjective risk perception and proposed three kinds of perception.Then it took use of empirical research methods of questionnaire to collect data to understand the consumers＇ perceived risk state of different food categories,and used the method of neural network to construct a neural network classifier where the classification accuracy is very high,in the future,the classifier would be used to classify consumer food safety risk perception in order to take practical and effective measures.