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- W2364009209 abstract "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." @default.
- W2364009209 created "2016-06-24" @default.
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- W2364009209 date "2008-01-01" @default.
- W2364009209 modified "2023-10-03" @default.
- W2364009209 title "Automatic recognition of stored-grain pests based on extension decision theory" @default.
- W2364009209 hasPublicationYear "2008" @default.
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