Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Taili ZHANG"'
Publikováno v:
Shuiwen dizhi gongcheng dizhi, Vol 51, Iss 4, Pp 197-205 (2024)
In the southeast coast of China, typhoon rainstorms resulted in lots of landslides. Investigating rainfall thresholds and patterns of typhoons is of great importance for the early warning of landslides. In this study, the landslide information obtain
Externí odkaz:
https://doaj.org/article/17f45ec9ec784627b0cbebbda742048e
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 3, Pp 877-894 (2024)
The aim of this study is to investigate the impacts of the sampling strategy of landslide and non-landslide on the performance of landslide susceptibility assessment (LSA). The study area is the Feiyun catchment in Wenzhou City, Southeast China. Two
Externí odkaz:
https://doaj.org/article/142368ff7a8b4bf28269f17de3360502
Autor:
Xiangren MENG, Zongzhen LIU, Peng WU, Zhicheng XU, Hengpeng WANG, Ziwu GAO, Danxuan WU, Sumin GAO, Huan ZHANG, Taili ZHANG
Publikováno v:
Shipin gongye ke-ji, Vol 44, Iss 9, Pp 104-110 (2023)
To improve the quality of brine goose pre-products, the following treatment groups were set up in the experiment: Tumbling ultrasonic compound marination method (G+C treatment group), tumbling marination method (G treatment group), ultrasonic marinat
Externí odkaz:
https://doaj.org/article/6bf36dbb133d455191845e557362a473
Autor:
Zizheng Guo, Yuanbo Liu, Taili Zhang, Juehao Zhang, Haojie Wang, Jun He, Guangming Li, Bixia Tian
Publikováno v:
Forests, Vol 15, Iss 5, p 791 (2024)
Typhoon-induced slope failure is one of the most important geological hazards in coastal areas. However, the specific influence of typhoons on the stability of residual soil slopes still remains an open issue. In this study, the Feiyunjiang catchment
Externí odkaz:
https://doaj.org/article/234da1ef604940f7848891881408e5ec
Publikováno v:
Water, Vol 15, Iss 8, p 1499 (2023)
Fractures are the dominant conditions for rainfall infiltration into slopes, which can aggravate the instability of landslides. However, few studies have been conducted to analyze in detail the instability and deformation characteristics of creeping
Externí odkaz:
https://doaj.org/article/6db132c8c0d44007839cbfc75a6a31dd
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 11, Iss 1, Pp 510-534 (2020)
Machine learning models are regarded as efficient and popular models for natural disaster susceptibility prediction. However, few studies have focussed on the applications of the latest popular machine learning models in collapse susceptibility asses
Externí odkaz:
https://doaj.org/article/b3c55ba5054c4a6086927215a65d3052
Publikováno v:
Landslides. 18:2565-2574
At about 04:00 on 10 August 2019, the heavy rainfall carried by Typhoon Lekima induced a catastrophic rockslide in Shanzao Village, Yongjia County, China. The heavy rainfall triggered the tuff rock mass of about 12×104 m3 in volume sliding along the
Publikováno v:
Bulletin of Engineering Geology and the Environment. 79:5259-5276
Intrusive granite dykes and their weathered layers can have great effects on seepage into slopes and on their stability. However, few studies of this topic have been reported. Using the Zhonglincun landslide as an example, we investigate the impact o
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 11, Iss 1, Pp 510-534 (2020)
Machine learning models are regarded as efficient and popular models for natural disaster susceptibility prediction. However, few studies have focussed on the applications of the latest popular machine learning models in collapse susceptibility asses
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030452926
Technologies of Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) are increasingly applied in urban construction and smart cities. As one of the high fidelity revivification methods, the purpose of these applications is to provide a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78084f2c73ada8ea76a8a3d27d446c66
https://doi.org/10.1007/978-3-030-45293-3_8
https://doi.org/10.1007/978-3-030-45293-3_8