An expert system with uncertain rules based on Dempster-Shafer theory

Author

Ahmadzadeh, Mohammad Reza ; Petrou, Maria

Author_Institution

Sch. of Electron. Ind., Shiraz Univ., Iran

Volume

2

fYear

2001

fDate

2001

Firstpage

861

Abstract

We study the aggregation of spatial remote sensing data (slope, aspect, soil depth and rock permeability) to assess the risk of desertification of a burned forest by an expert system. Belief functions which are assigned to data classes are propagated through expert rules. Uncertainty in data because of subsampling error and uncertainty in rules are considered during the processes. Experiments show the effectiveness of taking into consideration the uncertainty in data and rules

Keywords

belief maintenance; expert systems; geophysical signal processing; geophysical techniques; geophysics computing; image processing; remote sensing; terrain mapping; uncertainty handling; Dempster-Shafer theory; aggregation; belief functions; burned forest; desertification; expert system; geophysical measurement technique; image processing; land surface; remote sensing; risk; spatial data; terrain mapping; uncertain rules; uncertainty; Belief propagation; Character generation; Expert systems; Geographic Information Systems; Interpolation; Knowledge based systems; Permeability; Remote sensing; Soil; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.976661

Filename

976661