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| Format: | Artículo científico |
| Language: | en |
| Published: |
Instituto Politécnico Nacional
2007
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| Online Access: | https://www.redalyc.org/articulo.oa?id=61509707 |
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Table of Contents:
- Growth Evaluation of a Conifer Forest (Pinus Cooperí Blanco) using a Neural Net Backpropagation Trained with Distance Independent Competition Measures Jesús Celis Porras Computación Pinus Cooperí Blanco backpropagation neural net independent distance competition measures To make a decision about irregular forest handling practices is very difficult cause of some characteristics like age, natural life size diversity, and spatial distribution. A very important factor to fix growth forest is the competition about natural resources, so competition between trees should be considered to develop growth model. This is possible making use of parameters building with tree dimensions like diameter high, canopy extent, top high. These parameters are the distance independent competition measures. This research shows results product to use of backpropagation neural net trained with distance independent competition measures to forecast diameter and high growth. In this work we develop a growth model of a natural mixed forest of Pinus Cooperí Blanco, endemic specie of mountain region of Durango State, Mexico. This specie has been barely studied and is very important in wood exploitation production, because is used in timber wood production, and triplay fabrication. 2007 otro 1405-5546 https://www.redalyc.org/articulo.oa?id=61509707 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.4 Vol.10