具有可信度分析的卷烟质量评估模型预测控制方法

Predictive Control Method with Credibility in Cigarette Sensory Evaluation

为了改善大多数已建模型在预测时出现盲目的、机械的预测错误情况,以不同产地烤烟和白肋烟数据作为实验样本,综合集成假设检验、凸壳构造与内点分析、序列随机性检验等理论和方法,在预测控制环节设计了具有拒绝识别和可信度分析特征的分类器预测控制算法。实验结果表明,分类器能有效地接受与训练数据相似的测试样本,并给出凸壳内点测试样本的预测值和可信度参考值,同时亦能准确拒绝识别与烤烟质量数据差异较大的白肋烟和特异香型烤烟样本。不同类型测试数据实验验证了该算法的可行性和有效性,尤其是对于以专家经验或领域知识为主的卷烟质量评价问题更加实用。

In order to improve mechanical and blind prediction behavior of some built models, a classifier prediction control algorithm was designed with flue-cured tobacco and burley tobacco in different producing areas as experimental samples. It had the characteristic of rejecting recognition and credibility analysis through integrating several theories and methods including hypothesis testing, convex hull, interior point analysis and sequence random testing. The results demonstrated that classifier could effectively accept test sample set and give predictive values and reliability reference values of test data in convex hull. In the meanwhile, classifier could also accurately reject burley tobacco sample and special type flue-cured sample, which was different from flue-cured sample set. The feasibility and validity of classifier were verified through different type of testing data, especially the practicality of cigarette sensory evaluation was based on expert experience or domain knowledge.