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Retrieval of water quality parameters by neural network and analytical algorithm in Guanting Reservoir in Hebei Province in China

机译:基于神经网络和分析算法的河北省官厅水库水质参数反演

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Based on the measured spectra in the research area of Guangting reservoir, we build the model to retrieve chlorophyll-a, suspended solid and yellow substance. The paper mainly achieved the following results: we adopted matrix inversion method and L-M & NN method to analyse the water quality parameters, the selection schemes of the spectral band include REF, DER, RAN method, and then use the Guanting Reservoir experiment data for inspection and comparative analysis. The results showed that: the retrieval accuracy of L-M & NN method was better than matrix inversion method for three ocean color elements, the RAN weighted method overall had better retrieval accuracy. For C, acdom (440), the best scheme in band selection is RAN, REF showed better retrieval accuracy for Cs.
机译:基于广坪储层研究领域的测量光谱,我们构建模型以检索叶绿素-A,悬浮固体和黄色物质。本文主要实现以下结果:我们采用矩阵反转方法和LM&NN方法来分析水质参数,光谱频带的选择方案包括REF,DER,RAN方法,然后使用致命储层实验数据进行检查和比较分析。结果表明:L-M&NN方法的检索精度优于三个海洋颜色元素的矩阵反转方法,整体上的RAN加权方法具有更好的检索精度。对于C,ACDOM(440),频带选择的最佳方案是RAN,REF显示了CS的更好的检索精度。

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