Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Shufa Sun"'
Publikováno v:
Geoderma, Vol 450, Iss , Pp 117050- (2024)
Due to climate change, human activities and natural disturbances in high-latitude permafrost and seasonally frozen areas are gradually increasing, attracting more attention from scholars. However, research primarily focuses on soil biology and chemis
Externí odkaz:
https://doaj.org/article/50e90ed97a9d481194d062e9576bd585
Autor:
Xinyu Wang, Xinquan Wang, Mingxian Zhang, Chun Tang, Xingdong Li, Shufa Sun, Yangwei Wang, Dandan Li, Sanping Li
Publikováno v:
Fire, Vol 6, Iss 6, p 237 (2023)
Fire spread prediction is a crucial technology for fighting forest fires. Most existing fire spread models focus on making predictions after a specific time, and their predicted performance decreases rapidly in continuous prediction due to error accu
Externí odkaz:
https://doaj.org/article/f25cc7f21dc341d58aae7f4502f56290
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 11198 (2022)
To decrease track derailment of tracked fire trucks in forested areas, a fish-bellied swing arm torsion bar suspension system is proposed in this research. Derived from a tracked forest fire engine, this study converts the shaft tube swing arm of the
Externí odkaz:
https://doaj.org/article/da99349ac7d14742947b8b778db8b339
Publikováno v:
Advances in Materials Science and Engineering, Vol 2020 (2020)
In electrical discharge machining (EDM), the working medium plays an important role in the material removal process. Lots of methods have been utilized to study this process, but a widely accepted explanation about this process has not been yet accom
Externí odkaz:
https://doaj.org/article/448179a1ab0a4f1796f997c9c846d8d9
Publikováno v:
World Electric Vehicle Journal, Vol 13, Iss 2, p 27 (2022)
At present, most studies are focused on converting the vehicle kinetic energy into electrochemical energy for battery storage. During each deceleration period, the kinetic energy is first converted into electromagnetic energy and then stored in the c
Externí odkaz:
https://doaj.org/article/87e3503990df4a60973a8f3d2510c920
Publikováno v:
Fire, Vol 5, Iss 1, p 13 (2022)
The simulation of forest fire spread is a key problem for the management of fire, and Cellular Automata (CA) has been used to simulate the complex mechanism of the fire spread for a long time. The simulation of CA is driven by the rate of fire spread
Externí odkaz:
https://doaj.org/article/a5cdc4b7c27c46a5b8a908a2bd010c10
Autor:
Xingdong Li, Hewei Gao, Mingxian Zhang, Shiyu Zhang, Zhiming Gao, Jiuqing Liu, Shufa Sun, Tongxin Hu, Long Sun
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4325 (2021)
Modeling forest fire spread is a very complex problem, and the existing models usually need some input parameters which are hard to get. How to predict the time series of forest fire spread rate based on passed series may be a key problem to break th
Externí odkaz:
https://doaj.org/article/797219ca3a504f9782a0df5107c41d23
Publikováno v:
Information, Vol 12, Iss 6, p 235 (2021)
A single VLP-16 LiDAR estimation method based on a single-frame 3D laser point cloud is proposed to address the problem of estimating negative obstacles’ geometrical features in structured environments. Firstly, a distance measurement method is dev
Externí odkaz:
https://doaj.org/article/e1b96406bc224d7f88a8ed869f2a9a85
Autor:
Xingdong Li, Chuanying Lin, Mingxian Zhang, Sanping Li, Shufa Sun, Jiuqing Liu, Tongxin Hu, Long Sun
Publikováno v:
Journal of Forest Research. 28:111-119
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70f80338794e0a97c3efe39baabd52b5
https://doi.org/10.1080/13416979.2022.2138096
https://doi.org/10.1080/13416979.2022.2138096
Autor:
Li, Xinyu Wang, Xinquan Wang, Mingxian Zhang, Chun Tang, Xingdong Li, Shufa Sun, Yangwei Wang, Dandan Li, Sanping
Publikováno v:
Fire; Volume 6; Issue 6; Pages: 237
Fire spread prediction is a crucial technology for fighting forest fires. Most existing fire spread models focus on making predictions after a specific time, and their predicted performance decreases rapidly in continuous prediction due to error accu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::b9ca3bdb5b37672e32312877576c8c21