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Aspen Bibliography
A Bayesian Belief Network advisory system for aspen regeneration
Document Type
Article
Journal/Book Title/Conference
Forest Science
Volume
37
Issue
2
First Page
627
Last Page
654
Publication Date
1991
Abstract
The probability-based Bayesian Belief Network (BBN) methodology is demonstrated to be an alternative to rule-based methods in forest management expert systems. Unlike a rule-based system, a BBN incorporates uncertainty in the knowledge and input data without sacrificing knowledge modularity. After reviewing the graph and probability theory needed to define a BBN as a joint distribution representable by a directed acyclic graph, an 11-variable network modeling Rocky Mountain aspen sucker density response to different management options is constructed. For a typical aspen site, the model's estimated marginal probabilities of sucker response exhibit values consistent with those expected. Finally, a BBN is shown to be fairly tolerant to small parameter errors, and a new method is given for BBN model validation. For. Sci. 37(2):627-654.
Recommended Citation
Haas, Timothy C. 1991. A Bayesian Belief Network advisory system for aspen regeneration. Forest Science. 37 (2): 627-654.