Name
Title | ||
|---|---|---|
Predicting the hydrological response of a forest after wildfire and soil treatments using an Artificial Neural Network |
Abstract | ||
|---|---|---|
•Artificial Neural Networks (ANNs) have a low requirement of input information.•An ANN model purposely prepared for forests of the Mediterranean environment is proposed.•The ANN model has been verified at the plot scale in pine forests of South-Eastern Spain.•The runoff and erosion prediction capacity of the ANN is excellent and robust.•The hydrological effects of all the simulated soil treatments have been predicted with accuracy. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compag.2020.105280 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Artificial intelligence,Hydrological modelling,Surface runoff,Erosion,Mulching,Logging | Journal | 170 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Demetrio Antonio Zema | 1 | 0 | 0.34 |
| Manuel Esteban Lucas-Borja | 2 | 0 | 0.34 |
| Lidia Fotia | 3 | 0 | 0.34 |
| Domenico Rosaci | 4 | 779 | 55.81 |
| Giuseppe M.L. Sarnè | 5 | 0 | 0.34 |
| Santo Marcello Zimbone | 6 | 0 | 0.34 |