Skip to page content
USDA Forest Service

Research & Development Treesearch

Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help - We Participate  Government Made Easy

Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (156 KB)

Title: Application of artificial intelligence to risk analysis for forested ecosystems

Author: Schmoldt, Daniel L.;

Date: 2001

Source: Risk Analysis in Forest Management. 49-74.

Publication Series: Miscellaneous Publication

Description: Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI) techniques have been applied to risk analysis owing to their ability to deal with uncertainty, vagueness, incomplete and inexact specifications, intuition, and qualitative information. This paper examines knowledge-based systems, fuzzy logic, artificial neural networks, and Bayesian belief networks and their application to risk analysis in the context of forested ecosystems. Disturbances covered are: fire, insects/diseases, meteorological, and anthropogenic. Insect/disease applications use knowledge-based system methods exclusively, whereas meteorological applications use only artificial neural networks. Bayesian belief network applications are almost nonexistent, even though they possess many theoretical and practical advantages. Embedded systems -that use AI alongside traditional methods are, not unexpectedly, quite common.

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • You may send email to to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)



Schmoldt, Daniel L. 2001. Application of artificial intelligence to risk analysis for forested ecosystems. Risk Analysis in Forest Management. 49-74.


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.