中文摘要：本文将太赫兹光谱技术与极端学习机（ELM）相结合，建立了一种无需样品预处理的转基因大豆油的快速无损鉴别方法。为了达到识别精度、泛化能力和训练复杂度之间的最佳平衡，本文采用了交叉验证法优化惩罚系数C和隐节点数L的参数组合。在选定的最优参数对（c＝0.12，L＝70）下，基于THz-ELM模型的转基因和非转基因大豆油样品的分类精度可达89%以上。研究结果表明，太赫兹光谱技术可替代PCR和ELISA等早期技术，并为区分非转基因和转基因豆油提供了一种新的综合工具。
外文摘要：In this paper terahertz (THz) spectroscopy methodology combined with extreme learning machine (ELM) was developed for the fast and nondestructive identification of transgenic soybean oils without any sample pretreatment. In order to achieve the optimum balance among the recognition accuracy, generalization ability and training complexity, leave-one-out cross validation was employed to optimize the parameter combination of penalty coefficient C and the number of hidden nodes L. With the selected optimal parameter pairs, (C = 0.12, L = 70), the classification accuracy of THz-ELM model for the transgenic and non-transgenic soybean oil samples in training set and predicting set can exceed 89% simultaneously. The results demonstrate that THz spectroscopy could be in the future an excellent replacement of the antecedent procedures, such as PCR and ELISA, and supply a new comprehensive tool to distinguish non-transgenic and transgenic soybean oils.
外文关键词：Terahertz (THz) Spectroscopy; Rapid Detection; Non-Transgenic and Transgenic Soybean Oils
作者：Zhou, Sheng-Ling; Zhu, Shi-Ping; Liu, Guang-Hao; 等
作者单位：Southwest Univ
期刊名称：JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS
期刊影响因子：0.497
出版年份：2017
出版刊次：9