四种客观权重确定方法在粮虫可拓分类中的应用比较

Comparison of four methods for deciding objective weights of features for classifying stored-grain insects based on extension theory

储粮害虫的数字特征多,特征之间混合度比较大,可用可拓决策分析来解决其分类问题。在粮虫的可拓分类中,需要自动确定特征的客观权重,以避免传统的专家经验法在确定权重方面所带来的人为因素的影响。该文提出了模糊决策矩阵和均值决策矩阵2种构建决策矩阵的方法。将最大离差法、类间标准差法、CRITIC法和熵值法4种确定客观权重的方法分别应用到粮虫的分类中,并通过基于经典域和节域不同构建方法的2种可拓分类器进行了分析和比较。对粮仓中危害严重的9类粮虫进行了自动分类,结果表明基于模糊决策矩阵的最大离差法权重是粮虫可拓分类的最佳方案,识别率达到93%。

The extension theory can be used to solve the problem of recognition of the stored-grain insects that have many different features with overlapping attributes. It is necessary to determine the objective weights of the features in the classification based on extension theory, avoiding the human factor from the traditional method of expert evaluation. Two methods for constructing the fuzzy decision matrix and the mean decision matrix were put forward. Four methods for deciding objective weights of the features, namely, the methods of maximizing deviations, standard variance between-class, criteria importance through inter-criteria correlation and the entropy, were used to classify the grain-stored insects. These four methods were applied to the two extension-theory classifiers for the stored-grain insects based on two methods for constructing standard and extensional matter-element matrices. The nine species of the stored-grain insects in the grain-storage bin were automatically recognized by the classifier based on the extension theory The results showed that the maximizing deviation method for objective weights of features based on fuzzy decision matrix was the optimum scheme, and the correct identification ratio reached 93%.