Zobrazeno 1 - 5
of 5
pro vyhledávání: '"RACHID EL CHAAL"'
Publikováno v:
Journal of Environmental Engineering and Landscape Management, Vol 30, Iss 4 (2022)
This paper describes how the multilayer perceptron neural network (MLPNN) trained by the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-newton back-propagation approach was used to estimate heavy metal concentrations: Aluminum (Al), Lead (Pb), Copper
Externí odkaz:
https://doaj.org/article/c28d6b78689e4072a2fa6532d4eccaad
Autor:
RACHID EL CHAAL, M. O. Aboutafail
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 4, Iss 2 (2022)
Self-organizing maps (SOMs) and other artificial intelligence approaches developed by Kohonen can be used to model and solve environmental challenges. To emphasize the classification of Physico-chemical parameters of the Inaouen watershed, we present
Externí odkaz:
https://doaj.org/article/9f7f685b4c8047d6bad47baa6615fa5c
This paper adopts two modeling tools, namely, multiple linear regression (MLR) and artificial neural networks (ANNs), to predict the concentrations of heavy metals (zinc, boron, and manganese) in surface waters of the Oued Inaouen watershed flowing t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f458c394da3a7a92726dd8a92c27d099
https://doi.org/10.31219/osf.io/dk8mq
https://doi.org/10.31219/osf.io/dk8mq
Autor:
Rachid EL CHAAL
Publikováno v:
Communications in Mathematical Biology and Neuroscience.
Publikováno v:
E3S Web of Conferences, Vol 314, p 02001 (2021)
The principal purpose of this study is to build stochastic neuronal models, for the prediction of heavy metal, contents in the surface waters of the Oued Inaouen catchment area of the TAZA region, according to their Physico-chemical parameters; we ha