Name
Abstract | ||
|---|---|---|
This paper presents a method integrating artificial neural network (ANN) in cellular automata (CA) to simulate land use changes in Luxembourg and the areas adjacent to its borders. The ANN is used as a base of CA model transition rule. The proposed method shows promising results for prediction of land use over time. The ANN is validated using cross-validation technique and Receiver Operating Characteristic (ROC) curve analysis, and compared with logit model and a support vector machine approach. The application described in this paper highlights the interest of integrating ANNs in CA based model for land use dynamic simulation. |
Year | Venue | Keywords |
|---|---|---|
2012 | SpringSim (ANSS) | land use change,cellular automaton,logit model,land use dynamic simulation,cross-validation technique,ca model transition rule,receiver operating characteristic,artificial neural network,simulating land use change,land use,cellular automata |
Field | DocType | Volume |
Cellular automaton,Receiver operating characteristic,Computer science,Support vector machine,Artificial intelligence,Selection rule,Artificial neural network,Dynamic simulation,Land use | Conference | 44 |
Issue | ISSN | Citations |
2 | 0735-9276 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Omar Charif | 1 | 10 | 1.61 |
| Hichem Omrani | 2 | 89 | 7.91 |
| Reine-Maria Basse | 3 | 3 | 0.77 |