Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help
 

GeoTreesearch


Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

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

Publication Information

(246 KB bytes)

Title: Enhancing the Scientific Process with Artificial Intelligence: Forest Science Applications

Author: McRoberts, Ronald E.; Schmoldt, Daniel L.; Rauscher, H. Michael

Date: 1991

Source: AI Applications. 5(2): 5-26

Publication Series: Miscellaneous Publication

Description: Forestry, as a science, is a process for investigating nature. It consists of repeatedly cycling through a number of steps, including identifying knowledge gaps, creating knowledge to fill them, and organizing, evaluating, and delivering this knowledge. Much of this effort is directed toward creating abstract models of natural phenomena. The cognitive techniques of AI, with their emphasis on knowledge and thinking, can help scientists create, manipulate, and evaluate these models. The steps of the scientific process can be enhanced with five cognitive techniques from AI: neural networks, machine learning, advisory systems, knowledge management, and qualitative simulation. For each technique, we identify the steps of the scientific process to which it can be applied, provide background for the technique, and identify current or potential applications in forestry.

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 pubrequest@fs.fed.us to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)

XML: View XML

Citation:


McRoberts, Ronald E.; Schmoldt, Daniel L.; Rauscher, H. Michael 1991. Enhancing the Scientific Process with Artificial Intelligence: Forest Science Applications. AI Applications. 5(2): 5-26

 


 [ 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.