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Remote sensing retrieval of suspended solids in Longquan Lake based on GA-SVM model

机译：基于GA-SVM模型的龙泉湖悬浮物遥感反演

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This paper uses the GA-SVM inversion model to invert the suspended matter concentration in Longquan Lake. Genetic algorithm (GA) optimizes the parameters of the SVM inversion model to establish the new GA-SVM inversion model, and GA can effectively improve the efficiency and the accuracy of the SVM inversion model. The inversion model was established by using the measured hyperspectral data and suspended matter concentration. Comparing with SVM inversion model, GA-SVM inversion model achieves a better result in the application of suspended solids concentration inversion. Finally we uses GF-1 remote sensing images to retrieve suspended matter concentration in Longquan lake based on GA-SVM inversion model.
机译：本文采用GA-SVM反演模型对龙泉湖的悬浮物浓度进行反演。遗传算法优化了SVM反演模型的参数，建立了新的GA-SVM反演模型，GA可以有效地提高SVM反演模型的效率和准确性。利用测得的高光谱数据和悬浮物浓度建立了反演模型。与SVM反演模型相比，GA-SVM反演模型在悬浮物浓度反演的应用中取得了较好的效果。最后，基于GA-SVM反演模型，利用GF-1遥感图像提取龙泉湖中悬浮物浓度。

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