TY - JOUR
T1 - Analysis of multi-interpretable ecological monitoring information
AU - Brazier, F.
AU - Engelfriet, J.
AU - Treur, J.
PY - 2002/1
Y1 - 2002/1
N2 - In this paper logical techniques developed to formalize the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of samples of plant species that are observed. The logical foundation of this system is described in terms of a belief set operator and a selection operator.
AB - In this paper logical techniques developed to formalize the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of samples of plant species that are observed. The logical foundation of this system is described in terms of a belief set operator and a selection operator.
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U2 - 10.1080/088395102753365780
DO - 10.1080/088395102753365780
M3 - Article
SN - 0883-9514
VL - 16
SP - 29
EP - 50
JO - Applied Artificial Intelligence
JF - Applied Artificial Intelligence
IS - 1
ER -