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基于GA-PLS算法的河网水体化学需氧量高光谱反演
Authors
何甜辉
冯志伟
+6 more
刘海龙
姜波
蔡建楠
邢前国
陈文杰
黎倬琳
Publication date
1 January 2020
Publisher
Abstract
【目的】建立河网水体化学需氧量(COD)高光谱反演模型,验证遗传-偏最小二乘(GA-PLS)算法对建模效果的改善作用。【方法】采集广东省中山市146个点位的水体高光谱数据和COD质量浓度实测数据,通过GA-PLS算法对高光谱反射率数据进行特征波段筛选后建立COD质量浓度反演模型,并比较输入变量为不同特征波段组合时模型反演效果差异。【结果】基于GA-PLS算法的COD质量浓度高光谱模型反演效果优于全谱段PLS模型,验证集RMSEP最小为4.887 mg/L,较全谱段PLS模型降低11.4%;以筛选得到的74个波段(占全波段数的2.9%)作为输入变量时,模型仍可保持良好的稳定性和反演精度;GA-PLS算法筛选得出的部分特征波段与水体中藻类、悬浮颗粒物的吸收特征波段一致,筛选结果具有合理性和指示意义。【结论】通过GA-PLS算法可对高光谱数据进行特征波段筛选,实现数据降维优化,进一步简化模型;在样本COD质量浓度主要分布范围内,GA-PLS算法模型有良好的反演精度和水质类别分类准确性。该方法在河流COD快速监测中具有良好的应用前景
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Institutional Repository of Yantai Institute of Coastal Zone Research, CAS
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oai:ir.yic.ac.cn:133337/28204
Last time updated on 24/06/2021
Institutional Repository of Yantai Institute of Coastal Zone Research, CAS
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:ir.yic.ac.cn:133337/28202
Last time updated on 24/06/2021