| Autor: |
Bidyuk, P. I., Korshevnyuk, L. O., Fefelov, A. O., Litvinenko, V. I. |
| Předmět: |
|
| Zdroj: |
Naukovi visti NTUU - KPI; 2011, Vol. 2011 Issue 2, p36-45, 10p |
| Abstrakt: |
A generalized information technology for building artificial immune systems for solving problems of technical diagnosis is proposed. The technology allows creating a mathematical description of the drift parameters and detecting anomalies in the operation of complex technical systems. The novel method and algorithm for detecting the location and type of failure of complex engineering system with Bayesian networks and information content criteria are created. The information technology for neural networks development based on the theory of immune systems is developed. Specifically, this technology is employed to meet the challenges of forecasting parameters drift of the technical object. A combined method and algorithm for detecting anomalies in controlled parameters of the diagnosis based on clonal selection are elaborated. Finally, the computational model experiments for the developed methods, algorithms and information technologies are conducted. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
|
