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The Discrimination of Fluorescence Spectra of Phytoplankton for Environment Protection Based on the PCA and SVM

机译:基于PCA和SVM的环境保护浮游植物荧光光谱的辨别

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Issues of environmental protection and sustainable development are gaining an increasing importance in everyday life, and nowhere is this more than in the field of Materials Science and Engineering. The alga is the most common phytoplankton, identifying them can estimate the community structure and distribute status of ecosystem in the sea area and realize the inspecting and comprehensive father of sea. In this paper, the three dimension fluorescence spectra and principal component analysis method is combined to identify the ocean phytoplankton. Aiming at the east China sea, adopt the selection of common seaweed three-dimensional fluorescence spectrum of first principal component scores spectrum as bacillariophyta and pyrrophyta identification features diatoms and spectrum, established the phytoplankton fluorescence features spectrum library. On this basis, the SVM classifier is used to identify the kinds of the phytoplankton. The accuracy of the experimental results recognition is for 95%.
机译:环境保护和可持续发展问题正在日常生活中取得越来越重要,而且这不仅仅是材料科学与工程领域。藻类是最常见的浮游植物,鉴定它们可以估算海域生态系统的社区结构和分配状态,实现海上的检查和综合之父。本文将三维荧光光谱和主成分分析方法组合以鉴定海洋浮游植物。瞄准东海,采用普通海藻三维荧光谱的选择,第一主成分分数谱随杆菌病和辐射纤维素鉴定特征硅藻土和光谱,建立了浮游植物荧光特征光谱文库。在此基础上,SVM分类器用于识别浮游植物的种类。实验结果识别的准确性为95%。

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