A heuristic in rules based systems for searching of inconsistencies
Information Sciences—Informatics and Computer Science: An International Journal
Intrusion detection systems and multisensor data fusion
Communications of the ACM
Database aggregation of imprecise and uncertain evidence
Information Sciences—Informatics and Computer Science: An International Journal - special issue: Knowledge discovery from distributed information sources
IEEE Transactions on Knowledge and Data Engineering
Fault diagnosis using dynamic trend analysis: A review and recent developments
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Prediction-based diagnosis and loss prevention using qualitative multi-scale models
Information Sciences: an International Journal
A review of conflict detection and resolution modeling methods
IEEE Transactions on Intelligent Transportation Systems
A framework for fuzzy recognition technology
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Combining FDI and AI approaches within causal-model-based diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Appropriate choice of aggregation operators in fuzzy decision support systems
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Timely detecting information inconsistencies (anomalies) in real-time information provides strong support for decision-making in a dynamic decision-making situation. Existing techniques for information inconsistencies detection mainly focus on stored information by using a single structured-fixed descriptive model which always requires support from sufficient prior knowledge. The aim of this study is to develop a method for information inconsistencies detection for real-time information in dynamic decision-making situation where prior knowledge is insufficient by using multiple descriptive models. First, a rule-map technique is presented. A rule-map is a hierarchical directed graph, whose vertexes are selected descriptive models and whose arcs represent the covering relationship between descriptive models. A rule-map provides a strategy for selecting detecting descriptive models by means of the covering relationship and its structure is adjustable with the change in a situation. Then, a real-time information inconsistencies detection method, named RMDID, is developed based on the rule-map technique, which can take full advantage of multiple descriptive models. Finally, the proposed RMDID method is tested through two real cases. Experiments indicate that the proposed rule-map technique can trace the changes of a dynamic decision-making situation and the developed RMDID method can efficiently detect potential anomalies in real-time information.