Evaluating a model of forest succession using fuzzy analysis
Authors:
Jeong-Mi Yoon a;
Andr
de Korvin a
de Korvin a
| Affiliation: | a Department of Computer & Mathematical Sciences, University of Houston, Houston, TX, U.S.A. |
DOI:
10.1081/SAP-120000227
Publication Frequency:
6 issues per year
Published in:
Stochastic Analysis and Applications,
Volume
19,
Issue
5
October
2001
, pages 893
- 901
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Abstract
In this paper we discuss how to select the optimal policy from a set of possible policies for a model of forest succession, which can be characterized by a set of trees and the corresponding average life-span with each possible tree transition. The transition probabilities are estimated by counting the numbers of sapling trees of each species under a canopy tree. [1]. In our setting the transition matrix is defined by using the linguistic terms and as a consequence, the expected longevity of each tree is fuzzy. We use the Dempster-Shafer theory [8] ('76) together with techniques of Norton [7] ('88) and Smetz [9] ('76) to approximate the transition probabilities.
|
| Keywords: Fuzzy sets; Longevity; Markov chains; Transition probabilities; Stationary probabilities |
| view references (11) |

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