Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Mohamed Chaibi"'
Autor:
Abdenaim Minoubi, Nezha Mejjad, Khalid El Khalidi, Mohammed Bouchkara, Ahmed Fadili, Mohamed Chaibi, Bendahhou Zourarah
Publikováno v:
Oceans, Vol 4, Iss 4, Pp 331-349 (2023)
This study assesses the spatial distribution and contamination level of heavy metals in Safi Bay surface sediments. In this order, 28 surface sediment samples were retrieved from the study area and analyzed using the x-fluorescence method. To assess
Externí odkaz:
https://doaj.org/article/d66865d475ed4186981f94f7ce3478ad
Publikováno v:
International Journal of Renewable Energy Development, Vol 11, Iss 1, Pp 309-323 (2022)
Prediction of daily global solar radiation with simple and highly accurate models would be beneficial for solar energy conversion systems. In this paper, we proposed a hybrid machine learning methodology integrating two feature selection methods and
Externí odkaz:
https://doaj.org/article/1f063ccafaa7419eb3e3e5f26fc0c0b5
Publikováno v:
Energies, Vol 14, Iss 21, p 7367 (2021)
Machine learning (ML) models are commonly used in solar modeling due to their high predictive accuracy. However, the predictions of these models are difficult to explain and trust. This paper aims to demonstrate the utility of two interpretation tech
Externí odkaz:
https://doaj.org/article/b747539a9fcd4b4291320360fb351d14
Autor:
Barbara Theilen-Willige, Abdessamad Charif, Abdelhadi El Ouahidi, Mohamed Chaibi, Mohamed Ayt Ougougdal, Halima AitMalek
Publikováno v:
Geosciences, Vol 5, Iss 2, Pp 203-221 (2015)
The violent storms of 22–30 November 2014, resulted in flash floods and wadi floods (rivers) in large parts of Southern Morocco, at the foot of the Atlas Mountains. The Guelmim area was the most affected part with at least 32 fatalities and damages
Externí odkaz:
https://doaj.org/article/de415d000b3e40f0bffcb77360c25977
Autor:
Mohamed Chaibi, Mohamed Maanan, François Sabatier, Abdessamad Charif, Mohamed Ayt Ougougdal, Halima Ait Malek
Publikováno v:
Physio-Géo, Vol 8, Pp 101-119
Coastal dunes raise a special problem to scientists because of the high dynamic nature of most beach-dune systems. Coastal dunes can change shape quickly and frequently due to the violence of winds and waves during storms. This study analyses and int
Externí odkaz:
https://doaj.org/article/0dd7d6a98ce843bc851fc60b9ea9be32
Autor:
Hicham Gueddari, Mustapha Akodad, Mourad Baghour, Abdelmajid Moumen, Ali Skalli, Yassine El Yousfi, Hanane Ait Hmeid, Mohamed Chahban, Ghizlane Azizi, Mohamed Chaibi, Ouassila Riouchi, Mostapha Maach, Ahmed Ismail, Muhammad Zahid
Publikováno v:
Nature Environment and Pollution Technology. 21:2015-2023
The expansion of urbanization and the amplification of anthropic activities in the Rif region require the establishment of wells. However, the irrational exploitation of water and natural conditions have generated the rise of the water table and the
Autor:
Chaima Imam, Mohamed Chaibi, Mohamed Ayt Ougougdal, Fatima El Bchari, Abdessamad Charif, Halima Ait Malek
Publikováno v:
IECG 2022.
Publikováno v:
International Journal of Renewable Energy Development, Vol 11, Iss 1, Pp 309-323 (2022)
Prediction of daily global solar radiation with simple and highly accurate models would be beneficial for solar energy conversion systems. In this paper, we proposed a hybrid machine learning methodology integrating two feature selection methods and
Autor:
Yassine El Yousfi, Mahjoub Himi, Hossain El Ouarghi, Mourad Aqnouy, Said Benyoussef, Hicham Gueddari, Hanane Ait Hmeid, Abdennabi Alitane, Mohamed Chaibi, Muhammad Zahid, Narjisse Essahlaoui, Sliman Hitouri, Ali Essahlaoui, Abdallah Elaaraj
Publikováno v:
Sustainability; Volume 15; Issue 1; Pages: 402
Water quality index (WQI) is the primary method applied to characterize water quality in the world. The current study employed the statistical analysis and multilayer perceptron (MLP) approaches for predicting groundwater quality in the Ghiss-Nekkor
Publikováno v:
SSRN Electronic Journal.
Prediction of daily global solar radiation (H) with simple and high accurate models would be beneficial for solar energy conversion systems. In this paper, we proposed a hybrid machine learning methodology integrating two feature selection methods an