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首页> 外文会议>Target Recognition and Artificial Intelligence Summit Forum;Society of Photo-Optical Instrumentation Engineers >Modeling based on carbon content classification does not improve the prediction accuracy of carbon in intertidal zone sediments
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Modeling based on carbon content classification does not improve the prediction accuracy of carbon in intertidal zone sediments

机译：基于碳含量分类的模型不能提高潮间带沉积物中碳的预测精度

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The rapid prediction of carbon content by spectral method is helpful to grasp the carbon dynamic ofsediments in intertidal zone in a timely manner. The spectral reflectivity of sediments with high carboncontent and low carbon content often varies widely, limiting the accuracy of the model. When sedimentsamples are classified according to the carbon content and modeled separately, accurate prediction ofsediment carbon is expected to be achieved. However, previous studies have not reported it. In our study,sediment samples were divided into low-carbon and high-carbon sample sets according to 3 g/kg carboncontent, and divided into low-carbon, medium-carbon and high-carbon sample sets according to 2 g/kgand 4 g/kg carbon content, and then were pre-processed and PLS modeled separately. It is found thatthese classification can improve the modeling accuracy, but not improve the prediction accuracy. Theseresults can provide a technical reference for the prediction of sediment carbon in intertidal zone.
机译：通过光谱法快速预测碳含量有助于掌握碳动力学 及时地沉积在潮间区。高碳沉积物的光谱反射率 内容和低碳含量通常很大，限制了模型的准确性。沉积物时 样品根据碳含量进行分类，并单独建模，准确地预测 预计沉积物碳将实现。然而，之前的研究没有报告。在我们的研究中， 根据3g / kg碳，将沉积物样品分成低碳和高碳样品组 含量，并分为根据2g / kg的低碳，中碳和高碳样品组 和4g / kg碳含量，然后被预处理并分别建模。它被发现 这些分类可以提高建模精度，但不能提高预测准确性。这些 结果可以为潮间区预测沉积物碳的技术参考提供技术参考。

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