Methodology for implementing Virtual Sensors using Neural Networks

A. Pérez-Méndez, F. Rivas-Echevería, E. Colina-Morles, L. Nava-Puente, M. Olivares-Labrador

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)134-141
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2001
Externally publishedYes
EventApplications and Science of Computational Intelligence IV - Orlando, FL, United States
Duration: Apr 17 2001Apr 18 2001


  • Multivariate analysis
  • Neural Networks
  • Software engineering
  • Statistical analysis
  • Virtual Sensors

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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