Classification of pulsars using Extreme Deconvolution     

《New Astronomy》2022

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深水中极限波峰下速度场快速算法     

宁德志  滕斌  勾莹 《海洋工程》2009,27(3):62-65

基于五阶斯托克斯规则波理论,提出了一种快速求解深水极限波峰下速度场的数学模型.研究中,按照上跨零点和下跨零点的方法由计算或实测的极限波浪波面时间历程确定包含极限波峰的相邻两个周期的平均值为五阶斯托克斯规则波的波浪周期,然后根据极限波峰反推确定波浪入射波幅.通过与已有的数值结果和实验数据对比,验证了所建立的数值模型可以快速准确的计算出极限波峰下的速度场,相比其他模型,更适合于工程应用.  相似文献   

Multi-hazard susceptibility mapping based on Convolutional Neural Networks     

《地学前缘(英文版)》2022,13(5):101425

Multi-hazard susceptibility prediction is an important component of disasters risk management plan. An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions. However, with the rapid development of artificial intelligence technology, multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck. In order to effectively solve this problem, this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks (CNN). First, we use historical flash flood, debris flow and landslide locations based on Google Earth images, extensive field surveys, topography, hydrology, and environmental data sets to train and validate the proposed CNN method. Next, the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria, i.e., coefficient of determination, overall accuracy, mean absolute error and the root mean square error. Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods, debris flows and landslides. Finally, the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map. It can be observed from the map that 62.43% of the study area are prone to hazards, while 37.57% of the study area are harmless. In hazard-prone areas, 16.14%, 4.94% and 30.66% of the study area are susceptible to flash floods, debris flows and landslides, respectively. In terms of concurrent hazards, 0.28%, 7.11% and 3.13% of the study area are susceptible to the joint occurrence of flash floods and debris flow, debris flow and landslides, and flash floods and landslides, respectively, whereas, 0.18% of the study area is subject to all the three hazards. The results of this study can benefit engineers, disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.  相似文献