基于Tabu搜索的贝叶斯网络在烟叶香型评价中的应用OA北大核心CSCDCSTPCD
APPLYING TABU SEARCH-BASED BAYESIAN NETWORK IN APPRAISING AROMA TYPES OF TOBACCO
烟叶香型通常是靠人的嗅觉评定的,评定结果的准确性往往难以保证.针对该问题,国内外建立了BP神经网络等感官评估模型,但识别效率不高.根据烟叶中化学成分与烟叶香型关系,使用基于Tabu搜索的贝叶斯网络建立烟叶香型识别模型.实验结果表明,使用该方法能得到较好的贝叶斯网络结构,与BP神经网络等方法相比训练效率更高,分类的结果也更加准确.
The appraisal of aroma types of tobacco usually depends on olfaction, the veracity of its result is sometimes hard to be guaranteed. In view of this, sensory evaluation models have been constructed at home and abroad by using BP neural network or other methods, but they are inefficient in recognition. According to the relationship between chemical composition and the aroma types of tobacco, the recognition model of tobacco aroma types has been construc…查看全部>>
李丽华;丁香乾;贺英;王伟
中国海洋大学信息科学与工程学院,山东青岛266071中国海洋大学信息工程中心,山东青岛266071青岛大学电子学系,山东青岛266071中国海洋大学信息科学与工程学院,山东青岛266071
信息技术与安全科学
Tabu搜索贝叶斯网络烟叶香型
Tabu searchBayesian networkTobacco aroma types
《计算机应用与软件》 2012 (3)
225-227,3
评论