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Using neural Network techniques in Environmental Sensing and Measurement Systems to Compensate for the Effects of Influence Quantities

Dias Pereira, J. M. ; Postolache, O. ; Girão, P.M.

IEEE Instrumentation and Measurement Magazine Vol. 17, Nº 6, pp. 26 - 33, December, 2014.

ISSN (print): 1094-6969
ISSN (online):

Scimago Journal Ranking: 0,23 (in 2014)

Digital Object Identifier: 10.1109/MIM.2014.6968927

The environmental sensing and measurement systems are affected by multiple influence variables whose variations, over time, must be accounted in order to promote metrological comparability and traceability of measurement results. Suitable data processing techniques must be used to identify the main influence variables, that affect the measurement result of a given quantity, and to evaluate the associated compensation coefficients.