Belief Propagation in a Rule-based System Using The Dempster-Shafer Theory

Fusion 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 is studied. Belief functions which are assigned to data classes are propagated through expert rules. Uncertainty in the data because of sub-sampling error and uncertainty in the rules are considered during the processes. Experiments show the effectiveness of taking into consideration the uncertainty in data and rules

کلیدواژه ها:

Remote Sensing ، Dempster-Shafer Theory ، Belief Propagation ، Expert Systems