Classification and recognition of transgenic product by terahertz spectroscopy and DSVM |
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Authors: | Jianjun Liu Zhi Li Fangrong Hu Tao Chen Aijun Zhu |
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Affiliation: | 1. School of Mechano-Electronic Engineering, Xidian University, Xi’an, Shanxi 710071, PR China;2. Guilin University of Aerospace Technology, Guilin, Guangxi 541004, PR China;3. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, PR China |
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Abstract: | The purpose of this paper is to construct a classification model that can identify class accurately and control imbalance. A novel adaptive decision support vector machine (DSVM) is proposed for the recognition of transgenic cotton seed based on terahertz spectroscopy (THz), which make the traditional support vector machine is ability of adaptive decision, and select optimal parameters by using particle swarm optimization (PSO). For the classification and recognition of the transgenic cotton seeds, firstly, the factor analysis (FA) is applied to reduce the dimension and extract the feature spectrum of original spectral information. Secondly, the feature spectrum is selected and fed into the model of DSVM to recognize the different transgenic cotton seeds. The experimental results show that the proposed method can effectively classify the different transgenic cotton seeds, and its recognition rate surpasses the comparative method evidently. |
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Keywords: | DSVM PSO Terahertz Recognition Transgenic |
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