Zobrazeno 1 - 10
of 367
pro vyhledávání: '"m5p"'
Publikováno v:
مدیریت آب و آبیاری, Vol 14, Iss 3, Pp 665-679 (2024)
منابع آب زیرزمینی عامل مهمی در مدیریت و نگهداری آب است که برای آب آشامیدنی، آبیاری و سایر اهداف استفاده میشود. پیشبینی سطح آب زیرزمینی
Externí odkaz:
https://doaj.org/article/60e3376afa9040248eb81d069d7ca000
Autor:
Khabat Khosravi, Nasrin Attar, Sayed M. Bateni, Changhyun Jun, Dongkyun Kim, Mir Jafar Sadegh Safari, Salim Heddam, Aitazaz Farooque, Soroush Abolfathi
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e37965- (2024)
Accurate prediction of daily river flow (Qt) remains a challenging yet essential task in hydrological modeling, particularly crucial for flood mitigation and water resource management. This study introduces an advanced M5 Prime (M5P) predictive model
Externí odkaz:
https://doaj.org/article/53a053a30e1c46ecaa7b7bada105b288
Autor:
Carlos Roberto López Paredes, Cesar García, Kennedy C. Onyelowe, Maria Gabriela Zuniga Rodriguez, Tammineni Gnananandarao, Alexis Ivan Andrade Valle, Nancy Velasco, Greys Carolina Herrera Morales
Publikováno v:
Frontiers in Built Environment, Vol 10 (2024)
Industrial wastes have found great use in the built environment due to the role they play in the sustainable infrastructure development especially in green concrete production. In this research investigation, the impact of wastes from the industry on
Externí odkaz:
https://doaj.org/article/1cb85e7fab8542f58b75fc20e816d4d2
Autor:
Blaifi, Sid-ali a, ⁎⁎, Mellit, Adel b, ⁎, Taghezouit, Bilal c, Moulahoum, Samir d, Hafdaoui, Hichem c
Publikováno v:
In Renewable Energy 15 February 2025 240
Publikováno v:
Journal of Water and Health, Vol 22, Iss 4, Pp 639-651 (2024)
Stream flow forecasting is a crucial aspect of hydrology and water resource management. This study explores stream flow forecasting using two distinct models: the Soil and Water Assessment Tool (SWAT) and a hybrid M5P model tree. The research specifi
Externí odkaz:
https://doaj.org/article/474c71b681fa4e909235fb329bc58f78
Publikováno v:
Journal of Hydraulic Structures, Vol 9, Iss 1, Pp 98-110 (2023)
This study investigates the potential of Adaptive Neuro-fuzzy inference system (ANFIS), M5P, and Gaussian Process regression (GP) approaches to predict discharge coefficient (Cd) of chimney weir with different apex angles. Out of 110 data points, 77
Externí odkaz:
https://doaj.org/article/03de3d522ddc409180ebe56193960488
Akademický článek
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Publikováno v:
Journal of Soft Computing in Civil Engineering, Vol 6, Iss 4, Pp 43-58 (2022)
The current study uses machine learning techniques such as Random Forest Regression (RFR), Artificial Neural Networks (ANN), Support Vector Machines Ploy kernel (SVMP), Support Vector Machines Radial Basis Function Kernel (SVMRBK), and M5P model tree
Externí odkaz:
https://doaj.org/article/3fe14c000bce431fa550c62767c3d278
Publikováno v:
Water Supply, Vol 22, Iss 3, Pp 2707-2720 (2022)
The coefficient of Manning's roughness (n) has been generally implemented in the determination of depth and discharge in open channels and canals. This study unravels the novel idea and potential of Random Forest (RF), M5P, and Random Tree (RT) appro
Externí odkaz:
https://doaj.org/article/73ecf1ad6e4d4baa9b9c4a56706f2ab8
Publikováno v:
Water Supply, Vol 22, Iss 3, Pp 2847-2862 (2022)
Infiltration plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity. This study includes a comparative analysis of the two machine learning techniques, M5P model tree (M5P)
Externí odkaz:
https://doaj.org/article/e82e4aa7aff2416aa1086dd9b8ad4ee8