Research on Wheat Variety Classification based on KNN Algorithm
The paper establishes a mathematical model to accurately classify the test samples through parameters such as grain projection area,grain perimeter,grain compactness,grain length,grain width,asymmetry coefficient,grain trough length,and de-signs a mathematical algorithm for wheat grain recognition by analyzing the data to identify the grains of three different wheat varieties.First,the mathematical model for wheat variety classification is constructed,Then,the evaluation index of wheat varieties is construc-ted by using AHP,and the confusion matrix is used to evaluate successfully.Finally,the mathematical model of wheat varieties is op-timized by practical analysis.Through the analysis of the classification of three wheat varieties,Kama,Rosa and Canadians,after ex-cluding parameters such as perimeter and grain projection area,the model can be optimized to the greatest extent and the recognition rate of wheat varieties can be improved.
test samplesanalytic hierarchy processconfusion matrixmathematical model
万方数据
维普
