Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Mohamad Javad Alizadeh"'
Autor:
Mohamad Javad Alizadeh, Mohamad Reza Kavianpour, Malihe Danesh, Jason Adolf, Shahabbodin Shamshirband, Kwok-Wing Chau
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 12, Iss 1, Pp 810-823 (2018)
This study explores the river-flow-induced impacts on the performance of machine learning models applied for forecasting of water quality parameters in the coastal waters in Hilo Bay, Pacific Ocean. For this purpose, hourly recorded water quality par
Externí odkaz:
https://doaj.org/article/bd2d73c9ebd94908ac260bd03bd7e7c4
Publikováno v:
International Journal of Environmental Science and Technology. 19:2323-2336
Caspian Sea as the largest inland water body plays an important role in economy of its neighbor countries apart from its environmental significance. This study explores wave climate in three locations in the southern Caspian Sea considering the socio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fcd4c06d32c90b3126630d531f0e8c9
https://doi.org/10.1007/s13762-021-03314-1
https://doi.org/10.1007/s13762-021-03314-1
Publikováno v:
Energy. 262:125552
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9e704f5a14ad3f757010094ff9c2c8e
https://doi.org/10.1016/j.energy.2022.125552
https://doi.org/10.1016/j.energy.2022.125552
Publikováno v:
Ocean Engineering. 266:112821
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd1252d1eb66b29992955110052b263f
https://doi.org/10.1016/j.oceaneng.2022.112821
https://doi.org/10.1016/j.oceaneng.2022.112821
Publikováno v:
Asia-Pacific Journal of Atmospheric Sciences. 55:685-700
This study proposes a simple approach based on Weibull distribution parameters for downscaling climatic wind speed and direction. In this method, the Weibull parameters of a Global Climate Model (GCM) are modified using Weibull parameters of the refe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::266358e9982e6bbfd9a9e3a4cc0c7e18
https://doi.org/10.1007/s13143-019-00106-z
https://doi.org/10.1007/s13143-019-00106-z
Autor:
Kwok Wing Chau, Malihe Danesh, Jason E. Adolf, Mohamad Javad Alizadeh, Mohamad Reza Kavianpour, Shahabbodin Shamshirband
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 12, Iss 1, Pp 810-823 (2018)
This study explores the river-flow-induced impacts on the performance of machine learning models applied for forecasting of water quality parameters in the coastal waters in Hilo Bay, Pacific Ocean. For this purpose, hourly recorded water quality par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c73a46932330c9542a35dc15c2d6683
https://doi.org/10.1080/19942060.2018.1528480
https://doi.org/10.1080/19942060.2018.1528480
Publikováno v:
Journal of Hydroinformatics. 20:134-148
In this study, an integrated artificial neural network (IANN) model incorporating both observed and predicted time series as input variables conjoined with wavelet transform for flow forecasting with different lead times. The daily model employs fore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::737f2af38a00dc357639482497ae5aff
https://doi.org/10.2166/hydro.2017.142
https://doi.org/10.2166/hydro.2017.142
Publikováno v:
Proceedings of the Institution of Civil Engineers - Water Management. 170:150-162
River flow forecasting is important for successful water resources planning and management. The current study investigated the applicability of the artificial neural network (Ann), adaptive neuro-fuzzy inference system (Anfis), wavelet-Ann (Wann) and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c227418dac6dbaad38002d27b4041d0
https://doi.org/10.1680/jwama.14.00146
https://doi.org/10.1680/jwama.14.00146
A new approach for simulating and forecasting the rainfall-runoff process within the next two months
Publikováno v:
Journal of Hydrology. 548:588-597
In this study, a new approach is presented to predict rainfall and runoff in Tolt River basin within the next two months. For this purpose, a combination of wavelet transform and artificial neural network (WANN) incorporating both observed and predic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bed38b7f9ea6e8ceb0c0afe5482075b
https://doi.org/10.1016/j.jhydrol.2017.03.032
https://doi.org/10.1016/j.jhydrol.2017.03.032
Publikováno v:
Water Resources Management. 31:1777-1794
Accurate prediction of longitudinal dispersion coefficient (K) is a key element in studying of pollutant transport in rivers when the full cross sectional mixing has occurred. In this regard, several research studies have been carried out and differe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a4225ff52bffa091dd284c16ec2f77a
https://doi.org/10.1007/s11269-017-1611-z
https://doi.org/10.1007/s11269-017-1611-z