Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Uncertainly measures of rough set prediction
Artificial Intelligence
Rules in incomplete information systems
Information Sciences: an International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
A Review on Fault Diagnosis and Fault Tolerant Control Methods for Single-rotor Aerial Vehicles
Journal of Intelligent and Robotic Systems
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How to extract decision rules from incomplete decision table is of importance in fault diagnosis of helicopter transmission system. This paper introduces a knowledge acquisition method based on Granular Computing (GrC) for fault diagnosis of helicopter transmission system. First, following semantic analysis of missing attribute values in decision table, the basic idea of construction and interpretation of granules based on characteristic relation is studied. Then, the definition of GrC model based on characteristic relation as well as its construction algorithm is developed. Thus, a set of granules can be obtained completely and its implied information is consistent with the original decision table. Subsequently, the algorithm of attribute reduction in GrC is proposed. According to the definition of generalized decision rule, the way of extracting optimal decision rule from granules is studied. At last, Combined with an incomplete decision table for fault diagnosis of transmission system, this method has been achieved, and the analysis result shows its validity.