文章基本信息

标题：Knowledge Acquisition Approach Based on SVM in an Online Aided Decision System for Food Processing Quality and Safety
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作者：Liu Peng ; Liu Wen ; Yang Li 等
期刊名称：Cybernetics and Information Technologies
印刷版ISSN：1311-9702
电子版ISSN：1314-4081
出版年度：2014
卷号：14
期号：Special
DOI：10.2478/cait-2014-0049
出版社：Bulgarian Academy of Science
摘要：In connection with the problem that the food processing information system is poor due to the absence of knowledge acquisition and a knowledge self- updating function, a knowledge acquisition approach, based on a Support Vector Machine (SVM) is proposed. First, the approach establishes a set of predicted samples for the relationship between the food processing parameters and product quality; then it uses discretization of the continuous attributes, attributes reduction and a rule extraction algorithm of SVM to automatically acquire predicted knowledge from a large number of predicted sample sets. After that it saves the predicted knowledge in the knowledge base of an expert system; finally, the method realizes extraction of the knowledge about the food processing process based on the inference engine, which greatly enhances the efficiency and applicability of the acquired knowledge in an online aided decision system of food processing quality and safety.
关键词：Food processing; expert system; knowledge acquisition; SVM theory.