The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Jena: implementing the semantic web recommendations
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Towards Semantics-based Monitoring of Large-Scale Industrial Systems
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Distributed Reasoning for Context-Aware Services through Design of an OWL Meta-Model
ICAS '08 Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems
Managing uncertainty and vagueness in description logics for the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Pronto: a non-monotonic probabilistic description logic reasoner
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Cloud risk analysis by textual models
Proceedings of the 1st International Workshop on Model-Driven Engineering for High Performance and CLoud computing
Hi-index | 12.05 |
When a system instantaneous fails there is no time to perform preventative maintenance. In certain circumstances, where the system subsequently recovers without intervention, the system is left to run undiagnosed. Increasing the certainty of a particular diagnosis leads to a greater likelihood of the corrective action being carried out. Therefore, moving to a situation where available symptom and associated condition data is used to diagnose a failure is desirable. This paper proposes the implementation of a distributed network of semantic nodes that supports the inference of asset status. Querying is then performed to produce concrete facts regarding the status of the asset. The facts are used to support non-monotonic, probabilistic reasoning to increase the certainty that a particular symptom is the cause of the instantaneous failure.