基于可拓决策理论的储粮害虫自动识别

利用特征选择后粮仓害虫的10个形态学特征,在归一化分析的基础上,利用特征的均值和标准差来构造粮虫的经典物元和节域物元,提出了基于模糊分析定量确定特征权重系数的新方法.在计算待识别粮虫与各类粮虫的关联度的基础上,依据最大关联度准则对储粮害虫进行分类判别.并对粮仓中危害严重的9类粮虫进行了自动分类,识别率达到93%以上,结果表明,依据均值和标准差来构造粮虫的经典物元和节域物元可进一步提高识别的精度.

Automatic recognition of stored-grain pests based on extension decision theory

The ten morphological features of the stored-grain pests were normalized after selecting features.The standard and extensional matter-element matrixes were constructed based on the feature mean value and standard deviation.A quantitative method identifying the feature weight coefficients by fuzzy analysis was put forward.The correlative degrees between the stored-grain pests to be recognized and the nine species pests were calculated,such that the pests were classified according to the principle of the maximum correlative degree.The nine species of the stored-grain pests in grain-depot were automatically recognized by a classifier based on the extension decision theory,and the identification ratio was over 93%.The experiment showed that the recognition ratio can be improved by constructing standard and extensional matter-element matrixes based on the feature mean value and standard deviation.