Name
Abstract | ||
|---|---|---|
•There are large constraints in conventional direct methods of sediment deposition estimation.•In the present study, different data driven techniques were tried to find suitable model for sediment deposition estimation.•It was found that soft computing techniques can play important role in such modelling.•The evolutionary genetic programming technique found to the best modelling technique. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.asoc.2013.04.019 | Applied Soft Computing |
Keywords | Field | DocType |
Reservoir sedimentation,Soft computing techniques,Artificial neural networks,Model trees,Genetic programming | Soil science,Sediment,Mathematical optimization,Data-driven,Genetic programming,Sedimentation,Statistics,Artificial neural network,Piecewise linear function,Mathematics,Linear regression,Deposition (geology) | Journal |
Volume | Issue | ISSN |
13 | 8 | 1568-4946 |
Citations | PageRank | References |
3 | 0.43 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vaibhav Garg | 1 | 96 | 9.58 |
| V. Jothiprakash | 2 | 4 | 2.41 |