Understanding the geotechnical and geomechanical characteristics of erodible soils
A study incorporating soft computational modeling techniques
Bibliographic Data
| ID | 15110937 |
|---|---|
| Authors | Johnbosco C Egbueri (0000-0003-0281-1213, Chukwuemeka Odumegwu Ojukwu University, corresponding author), Mohd Yawar Ali Khan (0000-0001-6524-4733, King Abdulaziz University) |
| Year | 2023 |
| Volume | 26 |
| Issue | 2 |
| Pages | 4435-4466 |
| Publication date | 2023-01-03 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environment Development and Sustainability (JOURNAL) |
| Journal identifiers | ISSN: 1387-585X • E-ISSN: 1573-2975 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s10668-022-02890-7 |
| OpenAlex | W4313532074 |
| Language | EN |
| Citations received | 1 |
| References cited | 48 |
Artificial neural network · Cluster analysis · Geotechnical engineering · Machine learning · Principal component analysis · Soft computing · Soil water · Statistics · Computer Science · Dam Engineering and Safety · Environmental Science · Landslides and related hazards · Mathematics · Soil erosion and sediment transport · Geology · Soil Science
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |