In this study, a classification model for THz spectral data of coffee is constructed using an integrated learning approach, an AELM optimization model is proposed, the ELM is improved using the AO population optimization algorithm, the connection weights of the input and implicit layers of the ELM and the threshold of the implicit layer are searched for, the AELM is used as a weak classifier of FSAMME for integrated learning, the weights of the FSAMME algorithm are improved The update method is used to increase the weight of misclassified sample data and reduce the weight of weak classifiers with high classification error rate in the final classifier by dynamically weighting them during the iteration process according to the classification accuracy, and finally normalize all weak classifier weights to integrate the strong classifier AE-dynamic FS integrated learning model. The accuracy of AO-ELM-dynamic FSAMME model on the test set sample data set of five coffee origins is 99%, the classification accuracy of coffee samples from China, Brazil, Colombia, Ethiopia and Honduras is 100%, 100%, 100%, 94.4% and 100% respectively, and the number of samples misclassified is 1 sample from Ethiopia,realizing excellent classification performance.
Modern subaperture technologies mostly use the five-axis machine to follow the normal of state-of-the-art surfaces, such as aspheric, off-axis surfaces. The dual-tilt-axis tool has been widely used in optical manufacture to change the orientation of the tool. The initial tilt positions of the tool play an important role in the symmetry of tool influence function (TIF). The tilt angle errors may cause a skew TIF. We discussed the self-developed machine and its TIF models with different motion modes. Next, the effect of tilt angle errors, include spinning axis tilt error and revolution axis tilt error, was analyzed based on our self-developed polishing machine. Symmetric TIF will distort and form a skew TIF due to the angle error. There was a linear relationship between the eccentric ratio of the skew TIF and the angle error. In the experimental study, an initial adjustment was performed by utilizing a dial gauge, and then the TIF result showed that there were still some angle errors. We presented an image thresholding calibration method based on skew TIF to solve the tilt angle errors. After the new calibration, the following compared experiment got a fine symmetric, and Gauss-like TIF, and proved the validity of the proposed model and calibration method.
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