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Proceedings Paper

Methodology for implementing virtual sensors using neural networks
Author(s): Anna Perez-Mendez; Francklin Rivas-Echeverria; Eliezer Colina-Morles; Luis Nava-Puente; Marianilca Olivares-Labrador
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Paper Abstract

In this work a Methodology framework for implanting Virtual Sensors using Neural Networks will be presented, including the statistical analysis techniques that can be used for studying and processing the data. The proposed Methodology is based upon Software Engineering, Knowledge-based systems and neural networks methodologies. This methodological framework includes both technical and economical feasibility to build the virtual sensors and considers important aspects as the available computational platform, historical data files, data processing requirements such as filtering, pruning, set of variables that must be selected for the best performance of the virtual sensor, etc. There are also presented the statistical consideration and the corresponding techniques for data analysis and processing. The methodology includes techniques as principal components, cluster analysis, factorial analysis, etc.

Paper Details

Date Published: 21 March 2001
PDF: 8 pages
Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); doi: 10.1117/12.421162
Show Author Affiliations
Anna Perez-Mendez, Univ. de Los Andes (Venezuela)
Francklin Rivas-Echeverria, Univ. de Los Andes (Venezuela)
Eliezer Colina-Morles, Univ. de Los Andes (Venezuela)
Luis Nava-Puente, Univ. de Los Andes (Venezuela)
Marianilca Olivares-Labrador, Univ. de Los Andes (Venezuela)


Published in SPIE Proceedings Vol. 4390:
Applications and Science of Computational Intelligence IV
Kevin L. Priddy; Paul E. Keller; Peter J. Angeline, Editor(s)

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