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https://hdl.handle.net/20.500.14279/18408| Title: | Evaluation of the SRA tool using Data Mining Techniques | Authors: | Gregoriades, Andreas Sutcliffe, Alistair G. Karanikas, Haralampos |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Issue Date: | 2003 | Source: | 15th Conference on Advanced Information Systems Engineering (CAiSE '03), Klagenfurt/Velden, Austria, 16-20 June, 2003 | Conference: | Conference on Advanced Information Systems Engineering | Abstract: | This paper describes a validation approach of a socio-technical design support system using data mining techniques. Bayesian Belief Networks (BBN) are used to assess human error and system failure [13] based on a variety of high-level operational scenarios. The System Reliability Analyser (SRA) tool automates the process by iteratively manipulating the BBN model. Data mining techniques are employed in order to identify whether the initial assumptions embedded in the system reliability model are met by results from scenario-based testing. | URI: | https://hdl.handle.net/20.500.14279/18408 | Type: | Conference Papers | Affiliation : | University of Manchester |
| Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Evaluation_of_the_SRA.pdf | 31.63 kB | Adobe PDF | View/Open |
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