Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Saeed Khoshtinat"'
Autor:
Javad Hatamiafkoueieh, Salim Heddam, Saeed Khoshtinat, Solmaz Khazaei, Abdol-Baset Osmani, Ebrahim Nohani, Mohammad Kiomarzi, Ehsan Sharafi, John Tiefenbacher
Publikováno v:
Journal of Hydroinformatics, Vol 25, Iss 6, Pp 2643-2659 (2023)
In this study, the vote algorithm used to improve the performances of three machine-learning models including M5Prime (M5P), random forest (RF), and random tree (RT) is developed (i.e. V-M5P, V-RF, and V-RT). Developed models were tested for forecast
Externí odkaz:
https://doaj.org/article/98d3820ddf4e4daaa17796f9c0519007
Autor:
Solmaz Khazaei Moughani, Abdolbaset Osmani, Ebrahim Nohani, Saeed Khoshtinat, Tahere Jalilian, Zahra Askari, Salim Heddam, John P. Tiefenbacher, Javad Hatamiafkoueieh
Publikováno v:
Acta Geophysica.
Publikováno v:
Journal of Hydroinformatics. 21:745-760
The present research aims at applying three geographic information system (GIS)-based bivariate models, namely, weights of evidence (WOE), weighting factor (WF), and statistical index (SI), for mapping of groundwater potential for sustainable groundw
Publikováno v:
Journal of Earth System Science. 128
The goal of the present research is to evaluate three bivariate models of the frequency ratio, Shannon entropy (SE) and evidential belief function in the spatial prediction of groundwater at the Sero plain located in west Azerbaijan, Iran. In the fir