基于监督学习的紫外-可见光光谱水质在线异常检测方法研究

尹航, 俞巧君, 侯迪波^*, 黄平捷, 张光新, 张宏建

In-Situ Detection of Water Quality Anomaly with UV/Vis Spectrum Based on Supervised Learning

YIN Hang, YU Qiao-jun, HOU Di-bo^*, HUANG Ping-jie, ZHANG Guang-xin, ZHANG Hong-jian

苯酚紫外可见光谱(特征波长270 nm)===(a): 训练集和测试集原始数据; (b): 训练集和测试集校正后; (c): 测试集校正后去均值的时序展示