Effects of simultaneous incorporation of possibilistic and probabilistic uncertainty on decision making

B. Güneralp, George Gertner, Alan Anderson

Research output: Contribution to journalArticlepeer-review

Abstract

Possibilistic and probabilistic uncertainty are encountered in a variety of decision-making settings. A typical example is land classification analysis: the probabilistic uncertainty stems from various soil and vegetation data collected from the field and/or generated through simulation whereas the possibilistic uncertainty is due to the description of land condition on which a decision is to be made. The ma in objective of this study is to illustrate how incorporating fuzzy membership function to represent possibilistic uncertainty enhances the reliability of the analysis. A land classification analysis based on a previously developed methodology is used as a case study. The methodology enables handling both types of uncertainty: probabilistic uncertainty from the spatial simulation data and possibilistic uncertainty due to vagueness in land condition descriptions.

Original languageEnglish (US)
JournalUSDA Forest Service - General Technical Report PNW
Issue number688
StatePublished - Nov 2006

ASJC Scopus subject areas

  • Forestry
  • Ecology
  • Plant Science

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