Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Issam Rehamnia"'
Autor:
Issam Rehamnia, Ahmed Mohammed Sami Al-Janabi, Saad Sh. Sammen, Binh Thai Pham, Indra Prakash
Publikováno v:
HydroResearch, Vol 7, Iss , Pp 131-139 (2024)
In this study, three machine learning models, namely, the Multilayer Perceptron Neural Networks (MLPNN), the Generalized Regression Neural Networks (GRNN) and the Radial Basis Function Neural Networks (RBFNN) were used for predicting seepage flow thr
Externí odkaz:
https://doaj.org/article/9b4e0988614748a1aba071e84738a599
Publikováno v:
Environmental Processes. 7:367-381
The goal was to predict seepage flow (Q) through concrete face rockfill and embankment dams, using three artificial intelligence models, i.e., multivariate adaptive regression splines (MARS), least squares support vector machine (LSSVM), and M5 model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89b41f2e9ccc15b60e9b5347a415d91c
https://doi.org/10.1007/s40710-019-00414-6
https://doi.org/10.1007/s40710-019-00414-6
Publikováno v:
Measurement. 176:109219
Seepage flow through embankment dam is one of the most influential factors in failures of them. Thus, the monitoring and accurate measuring of seepage are crucial for the safety and construction cost of an embankment dam. In this study, an efficient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::202731e10112d03c7982ad9eebaf755e
https://doi.org/10.1016/j.measurement.2021.109219
https://doi.org/10.1016/j.measurement.2021.109219