PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Di Bono M. G., Pieri G., Salvetti O. A tool for system monitoring based on artificial neural networks. In: WSEAS Transaction on System, vol. 3 (2) pp. 746 - 751. WSEAS, 2004.
 
 
Abstract
(English)
A research has been carried out finalized to the definition of a methodology useful for the diagnosis and prediction of the correct evolution state of physical systems. In this paper we present a related model and a specific network topology for the considered problem. In particular, the prediction procedure is based on a 'Self Organizing Map'(SOM) and an 'Error Back-Propagation'(EBP) networks combined to form a hierarchical architecture. The network system has been developed and tested using data furnished by Alenia and consisting in sensorial data (FBG, Fiber Bragg Grating) and multi-format descriptive data regarding evaluation (SB). The obtained results have shown that the developed methodology is a promising tool for the diagnosis activity.
Subject Artificial Neural Networks
Self-Organising Maps
Prediction Systems
Life Cycle Monitoring
I.2 Artificial Intelligence
I.2.6 Learning
I.6.4 Model Validation and Analysis
C.3 Special-Purpose and Application-Based Systems


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