scholarly journals Multiple Kernel Learning with Maximum Inundation Extent from MODIS Imagery for Spatial Prediction of Flood Susceptibility

2021 ◽  
Author(s):  
Qiang Hu ◽  
Yuelong Zhu ◽  
Hexuan Hu ◽  
Zhuang Guan ◽  
Zeyu Qian ◽  
...  
Keyword(s):  
Multiple Kernel Learning ◽  
Spatial Prediction ◽  
Kernel Learning ◽  
Flood Susceptibility ◽  
Multiple Kernel ◽  
Modis Imagery ◽  
Inundation Extent

scholarly journals Multiple Kernel Learning with Maximum Inundation Extent from MODIS Imagery for Spatial Prediction of Flood Susceptibility

2021 ◽  
Author(s):  
Qiang Hu ◽  
Yuelong Zhu ◽  
Hexuan Hu ◽  
Zhuang Guan ◽  
Zeyu Qian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Yellow River ◽  
Multiple Kernel Learning ◽  
Spatial Prediction ◽  
Kernel Learning ◽  
Support Vector ◽  
Susceptibility Map ◽  
Remote Sensing Images ◽  
Flood Susceptibility ◽  
Multiple Kernel

Abstract This paper proposes a new technology of spatial prediction for flood susceptibility. Multiple kernel learning was used to build the flood susceptibility model and predict the flood inundation risk of the Sanhuajian Basin of the Yellow River. Based on the historical flow records of the Huayuankou Site and the MODIS remote sensing images of the study area, the maximum inundation range was extracted by the open water likelihood index method, and the flooded and non-flooded sample sites were selected. Considering the availability of pertinent literatures and data, ten flood conditioning factors were defined as the sample characteristics. The model performance was evaluated in terms of accuracy, F1 score, and AUC. According to the results, multiple kernel learning significantly outperforms the support vector machine adopting single kernel, and NLMKL demonstrates the best comprehensive performance. The flood susceptibility map generated by MODIS remote sensing images and multiple kernel learning, therefore, can provide effective help for researchers and decision makers in flood management.

Robust Subspace Clustering Based on Automatic Weighted Multiple Kernel Learning

2021 ◽  
Author(s):  
Guo ◽  
Xiaoqian Zhang ◽  
Zhigui Liu ◽  
Xuqian Xue ◽  
Qian Wang ◽  
...  
Keyword(s):  
Multiple Kernel Learning ◽  
Subspace Clustering ◽  
Kernel Learning ◽  
Multiple Kernel

scholarly journals Multiple Kernel Learning With Minority Oversampling for Classifying Imbalanced Data

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 565-580
Author(s):  
Ling Wang ◽  
Hongqiao Wang ◽  
Guangyuan Fu
Keyword(s):  
Multiple Kernel Learning ◽  
Imbalanced Data ◽  
Kernel Learning ◽  
Multiple Kernel

scholarly journals Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data

2014 ◽  
Author(s):  
Andrew D. O'Harney ◽  
Andre Marquand ◽  
Katya Rubia ◽  
Kaylita Chantiluke ◽  
Anna Smith ◽  
...  
Keyword(s):  
Multiple Kernel Learning ◽  
Kernel Learning ◽  
Multiple Kernel ◽  
Neuroimaging Data ◽  
Multiple Class
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