A decision theoretic framework for approximating concepts
International Journal of Man-Machine Studies
Communications of the ACM
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Evidence Theory and Its Applications
Evidence Theory and Its Applications
Managing Uncertainty in Expert Systems
Managing Uncertainty in Expert Systems
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
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Monitoring the mechanical impact of a loose (detached or drifting) part in the reactor coolant system of a nuclear power plant is one of the essential functions for operation and maintenance of the plant.Large data tables are generated during this monitoring process. This data can be "mined" to reveal latent patterns of interest to operation and maintenance. Rough set theory has been applied successfully to data mining. It can be used in the nuclear power industry and elsewhere to identify classes in datasets, finding dependencies in relations and discovering rules which are hidden in databases. This paper can be considered as one of a series, the earlier ones being summarized in Guan & Bell (2000a). These methods can be used to understand and control aspects of the causes and effects of loose parts in nuclear power plants. So in this paper we illustrate the use of our data mining methods by means of a running example using Envelope Rising Time data ERT on monitoring loose parts in nuclear power plants.