Abstract: This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used classic and statistical models.

Keywords: Neural Networks, clustering, Radial Basis Functions, Forest Inventory.

ACM Classification Keywords: I.5. Pattern Recognition – I.5.1. Neural Nets; I.5.3. Clustering

Link:

APPLICATIONS OF RADIAL BASIS NEURAL NETWORKS FOR AREA FOREST

Angel Castellanos, Ana Martinez Blanco, Valentin Palencia

http://www.foibg.com/ijita/vol14/ijita14-3-p04.pdf