On the Dempster-Shafer framework and new combination rules
Information Sciences: an International Journal
International Journal of Robotics Research - Special Issue on Sensor Data Fusion
Distance measures for signal processing and pattern recognition
Signal Processing
Application of Dempster—Shafer theory in condition monitoring applications: a case study
Pattern Recognition Letters
Applications of NDT Data Fusion
Applications of NDT Data Fusion
Uncertainty modelling using Dempster-Shafer theory for improving detection of weld defects
Pattern Recognition Letters
Uncertain inferences and uncertain conclusions
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Expert Systems with Applications: An International Journal
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Concept-based evidential reasoning for multimodal fusion in human-computer interaction
Applied Soft Computing
Intelligent Aircraft Damage Assessment, Trajectory Planning, and Decision-Making under Uncertainty
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Mass function derivation and combination in multivariate data spaces
Information Sciences: an International Journal
Intelligent condition monitoring and prognostics system based on data-fusion strategy
Expert Systems with Applications: An International Journal
SafeVchat: detecting obscene content and misbehaving users in online video chat services
Proceedings of the 20th international conference on World wide web
Combination rule of D-S evidence theory based on the strategy of cross merging between evidences
Expert Systems with Applications: An International Journal
A multilevel information fusion approach for visual quality inspection
Information Fusion
Agent oriented intelligent fault diagnosis system using evidence theory
Expert Systems with Applications: An International Journal
SafeVchat: A System for Obscene Content Detection in Online Video Chat Services
ACM Transactions on Internet Technology (TOIT)
Integrating textual analysis and evidential reasoning for decision making in Engineering design
Knowledge-Based Systems
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Engine diagnostics is a typical multi-sensor fusion problem. It involves the use of multi-sensor information such as vibration, sound, pressure and temperature, to detect and identify engine faults. From the viewpoint of evidence theory, information obtained from each sensor can be considered as a piece of evidence, and as such, multi-sensor based engine diagnosis can be viewed as a problem of evidence fusion. In this paper we investigate the use of Dempster-Shafer evidence theory as a tool for modeling and fusing multi-sensory pieces of evidence pertinent to engine quality. We present a preliminary review of Evidence Theory and explain how the multi-sensor engine diagnosis problem can be framed in the context of this theory, in terms of faults frame of discernment, mass functions and the rule for combining pieces of evidence. We introduce two new methods for enhancing the effectiveness of mass functions in modeling and combining pieces of evidence. Furthermore, we propose a rule for making rational decisions with respect to engine quality, and present a criterion to evaluate the performance of the proposed information fusion system. Finally, we report a case study to demonstrate the efficacy of this system in dealing with imprecise information cues and conflicts that may arise among the sensors.