Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Shuoben, Bi"'
Autor:
Karam Alsafadi, Shuoben Bi, Hazem Ghassan Abdo, Hussein Almohamad, Basma Alatrach, Amit Kumar Srivastava, Motrih Al-Mutiry, Santanu Kumar Bal, M. A. Sarath Chandran, Safwan Mohammed
Publikováno v:
Geoscience Letters, Vol 10, Iss 1, Pp 1-21 (2023)
Abstract Due to rapid population growth and the limitation of land resources, the sustainability of agricultural ecosystems has attracted more attention all over the world. Human activities will alter the components of the atmosphere and lead to clim
Externí odkaz:
https://doaj.org/article/aa875cedd8c5409183da7cad65cfbd63
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 13, Iss 1, Pp 621-645 (2022)
This paper presents an analysis based on the use of historical data of frost/snow disasters in North China in combination with ArcGIS and other technical applications. Specifically, the frequency and intensity of frost/snow disasters in North China d
Externí odkaz:
https://doaj.org/article/c3a7dc122e5c4346ae88a14d0bc1c0c3
Publikováno v:
Heliyon, Vol 9, Iss 7, Pp e17549- (2023)
This study provides an alternative agenda to better explain the Belt and Road Initiative's (BRI's) technological connotations in Bangladesh using the Game Theory and Demand Curve approaches. BRI can proceed as a means to technology development for Ba
Externí odkaz:
https://doaj.org/article/dd7ceec299504cc5a028c9dffe074cea
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract Taxi demand forecasting is crucial to building an efficient transportation system in a smart city. Accurate taxi demand forecasting could help the taxi management platform to allocate taxi resources in advance, alleviate traffic congestion,
Externí odkaz:
https://doaj.org/article/1a4e29df6bdd438689492c49d7b06dac
Autor:
Karam Alsafadi, Shuoben Bi, Bashar Bashir, Ehsan Sharifi, Abdullah Alsalman, Amit Kumar, Shamsuddin Shahid
Publikováno v:
Remote Sensing, Vol 15, Iss 9, p 2435 (2023)
The inclusion of physiographic and atmospheric influences is critical for spatial modeling of orographic precipitation in complex terrains. However, attempts to incorporate cloud cover frequency (CCF) data when interpolating precipitation are limited
Externí odkaz:
https://doaj.org/article/b4ea93e58b254b85832e8932ca44c21f
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 11, Iss 1, Pp 2509-2539 (2020)
The present study sought to understand the spatiotemporal characteristics, associated with changes in drought disasters during the Ming and Qing Dynasties in North China. The grade sequence of drought disasters at 21 sites for the given period (1470
Externí odkaz:
https://doaj.org/article/b138d41c360f4139aa00e684905be0fe
Autor:
Karam Alsafadi, Shuoben Bi, Bashar Bashir, Safwan Mohammed, Saad Sh. Sammen, Abdullah Alsalman, Amit Kumar Srivastava, Ahmed El Kenawy
Publikováno v:
Remote Sensing, Vol 14, Iss 24, p 6237 (2022)
Gross primary production (GPP) is a key component in assessing the global change in carbon uptake and in evaluating the impacts of climate change on terrestrial ecosystems. A decrease in the photosynthetic rate due to stomata closing by vegetation co
Externí odkaz:
https://doaj.org/article/469387733f634e119b9dd4fa1aa71c3d
Publikováno v:
Journal of Advanced Transportation, Vol 2021 (2021)
It is an important content of smart city research to study the activity track of urban residents, dig out the hot spot areas and spatial interaction patterns of different residents’ activities, and clearly understand the travel rules of urban resid
Externí odkaz:
https://doaj.org/article/8a713c864e134b5d9f12bd39bf1c7968
Publikováno v:
Journal of Advanced Transportation, Vol 2021 (2021)
In view of the fact that the density-based clustering algorithm is sensitive to the input data, which results in the limitation of computing space and poor timeliness, a new method is proposed based on grid information entropy clustering algorithm fo
Externí odkaz:
https://doaj.org/article/34d94ffde54745b0b4550e93b0962ea7
Autor:
Athanase Nkunzimana, Shuoben Bi, Mohamed Abdallah Ahmed Alriah, Tang Zhi, Ngong Awan Daniel Kur
Publikováno v:
Earth and Space Science, Vol 7, Iss 5, Pp n/a-n/a (2020)
Abstract This study aims to evaluate the performance of the Climate Hazards Group Infrared Precipitation with Station observation Version 2 (CHIRPS v2.0), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network
Externí odkaz:
https://doaj.org/article/18738fae69e94b75b1ea332abd1a29b3