Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Kai Lun Chong"'
Autor:
Yaxing Wei, Huzaifa Bin Hashim, Sai Hin Lai, Kai Lun Chong, Yuk Feng Huang, Ali Najah Ahmed, Mohsen Sherif, Ahmed El-Shafie
Publikováno v:
IEEE Access, Vol 12, Pp 10865-10885 (2024)
Deep learning excels at managing spatial and temporal time series with variable patterns for streamflow forecasting, but traditional machine learning algorithms may struggle with complicated data, including non-linear and multidimensional complexity.
Externí odkaz:
https://doaj.org/article/81f87b70401344f3a09a346c56796d1e
Autor:
Yuk Feng Huang, Jing Lin Ng, Kit Fai Fung, Tan Kok Weng, Nouar AlDahoul, Ali Najah Ahmed, Mohsen Sherif, Barkha Chaplot, Kai Lun Chong, Ahmed Elshafie
Publikováno v:
Applied Water Science, Vol 13, Iss 10, Pp 1-25 (2023)
Abstract Natural calamities like droughts have harmed not just humanity throughout history but also the economy, food, agricultural production, flora, animal habitat, etc. A drought monitoring system must incorporate a study of the geographical and t
Externí odkaz:
https://doaj.org/article/bb5b9df082db450599916713ff554490
Autor:
Nur Alyaa Hazrin, Kai Lun Chong, Yuk Feng Huang, Ali Najah Ahmed, Jing Lin Ng, Chai Hoon Koo, Kok Weng Tan, Mohsen Sherif, Ahmed El-shafie
Publikováno v:
Heliyon, Vol 9, Iss 9, Pp e19426- (2023)
In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. Data compiled from 1985 to 2018 was utilized for training and testi
Externí odkaz:
https://doaj.org/article/5c759a3b2a4c4094bac2bf98ca45a402
Autor:
Nasrin Adlin Syahirah Kasniza Jumari, Ali Najah Ahmed, Yuk Feng Huang, Jing Lin Ng, Chai Hoon Koo, Kai Lun Chong, Mohsen Sherif, Ahmed Elshafie
Publikováno v:
Heliyon, Vol 9, Iss 8, Pp e18424- (2023)
Cities are growing geographically in response to the enormous increase in urban population; consequently, comprehending growth and environmental changes is critical for long-term planning. Urbanization transforms naturally permeable surfaces into imp
Externí odkaz:
https://doaj.org/article/4bae913bbcdc49df9a131ab38e837010
Autor:
Wei Joe Wee, Kai Lun Chong, Ali Najah Ahmed, Marlinda Binti Abdul Malek, Yuk Feng Huang, Mohsen Sherif, Ahmed Elshafie
Publikováno v:
Applied Water Science, Vol 13, Iss 1, Pp 1-16 (2022)
Abstract Hydrologists rely extensively on anticipating river streamflow (SF) to monitor and regulate flood management and water demand for people. Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alon
Externí odkaz:
https://doaj.org/article/c79665a1e8c046cdb12b2cfbb4fb5ec8
Autor:
Kai Lun Chong, Sai Hin Lai, Ali Najah Ahmed, Wan Zurina Wan Zaafar, Ravipudi Venkata Rao, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie
Publikováno v:
IEEE Access, Vol 9, Pp 19488-19505 (2021)
In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the g
Externí odkaz:
https://doaj.org/article/c229168d429f4db385306db033dae96b
Autor:
Nur Amira Afiza Bt Saiful Bahari, Ali Najah Ahmed, Kai Lun Chong, Vivien Lai, Yuk Feng Huang, Chai Hoon Koo, Jing Lin Ng, Ahmed El-Shafie
Publikováno v:
Archives of Computational Methods in Engineering.
Autor:
Ravipudi Venkata Rao, Mohsen Sherif, Ahmed El-Shafie, Kai Lun Chong, Ali Najah Ahmed, Ahmed Sefelnasr, Sai Hin Lai, Wan Zurina Wan Zaafar
Publikováno v:
IEEE Access, Vol 9, Pp 19488-19505 (2021)
In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the g
Publikováno v:
Water Resources Management. 34:2371-2387
The core objective of this study is to carry out rainfall forecasting over the Langat River Basin through the integration of wavelet transform (WT) and convolutional neural network (CNN). The proposed method involves using CNN for feature extraction
Publikováno v:
Water Resources Management. 33:2015-2032
The main aim of this study is to perform a time series frequency analysis and assessment for stream flow over the Johor River using a comparative method between wavelet transform (WT) and Fourier transform (FT). One of the wavelet analyses used was t