%0 Conference Paper
%A DeCapua, Claudio
%E Romeo, Emilia
%I IEEE
%D 2006
%G English
%@ 9780780393592
%@ 0780393597
%@ 1091-5281
%T A Fuzzy Approach to represent Measurement Data affected by both A-type and B-type Uncertainty
%J 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings
%P 1484-1489
%U http://bonn.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NT8IwFG9EY6IxUUGjokkP3sjiYHOwIw6IHuQ0LyaGdGOLJLAR2WLgr_e9130U3MV4WbYeunbvt_Z9_srYfScwpkY3hP8b7B_NDLqG1vNDoUGz_-h7PlKKYbbF2B69W-7QHpe5qhjO_fQ2WvT1jSkW6GFLvfjfkoU2kC1Wyv5BukWn0AD3IGO4gpThuqMAV-41aKu30GKjsD8yIURZ_iBlUJQeQMWJrpT5yUIB6nSloqffGqWbzRqV1KLkivgvsVZpq9uBSERLUFaIVGa9GANBGvl2cQxP8vYN3kbZB0nhxB8EjlimpL06c5FOZUqYDP8spA93uJjNZ2LXNWGqrolf5iqoI7IUWPFoIjEpWMPy3JZsFW1LftN8R4ZHu3q1J7LUl1fXkVElo9OzTLPc2Yp8QzxiG3STGqsZWdCZNmqTiACKjRtrcik4no2IvDzZiLsZWVMxgzzkrdsPuwPYOqiH9BT3jF2UouWlaM_ZXhDV2Wl-hAfPVvQ6O1b4KOvskPKB_VWDffQ5AYDnAOBJzAsAcAUAHAHAcwBwb80RAFwCgAMAuAQAVwBwwZqjoes8aziByVISnkzw88GU9Ut2IrDuIkqoPnN6xXgA-qkFRqcwLd00AgM-TxuM3J7uty1f98Jr1qjq6qa6ucmOShzdsoMQftLgju17cRT9AAs6VRA
%X This paper proposes a new approach to transform the probability distribution of N repeated measurement results into a possibility distribution in presence of both A-type and B-type uncertainty. The technique presents the final measurement result in terms of a fuzzy set which easily expresses the levels of confidence for the final uncertainty to be determined as a-cuts. In this treatment the statistical independence of the measurement data permit the assumption that the samples are derived from a normal distribution. The fuzzy set representation of measurement uncertainty is preferable in cases where acquisitions have to be further processed and where, in these events, a conversion into symbolic format may be also necessary reasoning systems. As a case study, the propagation of uncertainty in presence of decision rules is considered
%K Computer science
%K Electric variables measurement
%K Fuzzy sets
%K Gaussian distribution
%K Instrumentation and measurement
%K Instruments
%K Lab-on-a-chip
%K Measurement uncertainty
%K Possibility distribution
%K Probability distribution
%K Shape measurement