Ruhollah Taghizadeh‐Mehrjardi
Biographic Data
| ID | 7715449 |
|---|---|
| NAME | Ruhollah Taghizadeh‐Mehrjardi |
| GIVEN NAMES | Ruhollah |
| FAMILY NAME | Taghizadeh‐Mehrjardi |
| SIGNATURE | MEHRJARDI R T |
| AFFILIATIONS | Ardakan University |
| ORCID | 0000-0002-4620-6624 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Machine Learning Applications in Archaeological Practices
Artificial intelligence and machine learning applications in archaeology have increased significantly in recent years, and these now span all subfields, geographical regions, and time periods: from prehistory to modern times. The prevalence and success of these applications have remained largely unexamined, as recent reviews on the use of machine learning in archaeology have only focused only on specific subfields of archaeology. Our review exami…
Salt dome related soil salinity in southern Iran
In order to manage soil salinity effectively, it is necessary to understand the origin and the spatial distribution of salinity. There are about 120 salt dome outcrops in southern Iran and little is known about their contribution as the potential sources of salts and the spatial pattern of salts around them. Six machine learning algorithms were applied to model topsoil electrical conductivity (EC) and sodium adsorption ratio (SAR) in the Darab Pl…
Impacts of vegetation anomalies and agricultural drought on wind erosion over Iran from 2000 to 2018
No prominent works on this page.
Impacts of vegetation anomalies and agricultural drought on wind erosion over Iran from 2000 to 2018
Salt dome related soil salinity in southern Iran
In order to manage soil salinity effectively, it is necessary to understand the origin and the spatial distribution of salinity. There are about 120 salt dome outcrops in southern Iran and little is known about their contribution as the potential sources of salts and the spatial pattern of salts around them. Six machine learning algorithms were applied to model topsoil electrical conductivity (EC) and sodium adsorption ratio (SAR) in the Darab Pl…
Machine Learning Applications in Archaeological Practices
Artificial intelligence and machine learning applications in archaeology have increased significantly in recent years, and these now span all subfields, geographical regions, and time periods: from prehistory to modern times. The prevalence and success of these applications have remained largely unexamined, as recent reviews on the use of machine learning in archaeology have only focused only on specific subfields of archaeology. Our review exami…
Environmental Science (2 works) · Geology (2 works) · Aeolian processes (1 work) · Aeolian processes and effects (1 work) · Anomaly (physics) (1 work) · Archaeological Research and Protection (1 work) · Archaeology and ancient environmental studies (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work) · Atmospheric aerosols and clouds (1 work)