Using Supervised Learning Techniques for Diagnosis of Dynamic Systems
作者： Rafael M Gasca , Juan A Ortega , Pedro J Abad , Antonio J Suarez
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摘要: Abstract : This paper describes an approach based on supervised learning techniques for the diagnosis of dynamic systems. The methodology can start with real system data or a model system. In second case, set simulations is required to obtain necessary data. both cases, obtained will be labelled according running conditions at gathering time. Label indicates state system: correct working abnormal functioning any component. After being labelled, treated add additional information about final goal decision rules by applying classification tool and way, observation classified those rules, having return label indicating currently Returned diagnostic. entire task carried out off-line, before diagnosing.
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