@inproceedings{
 title = {Odor recognition systems for natural gas odorization monitoring},
 type = {inproceedings},
 year = {2012},
 id = {41379446-f0d3-38ea-a5dd-ba55129e23a3},
 created = {2019-02-14T18:02:01.618Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:01.618Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper presents a system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants and details the development of the sensor and pattern recognition systems. The sensor system uses spectroscopic technology and the pattern recognition system uses wavelet and artificial neural network technology. The aim is to determine the concentration of a natural gas odorant in the environment and associate this concentration with the benchmark index, which measures the degree of human perception to the presence of gas in the environment. Experiments were conducted comparing the performance of the system with human performance, which is normally used to deal with this problem. The proposed system demonstrated promising results. © 2012 IEEE.},
 bibtype = {inproceedings},
 author = {Zanchettin, C. and Almeida, L.M. and Menezes, F.D. and Ludermir, T.B. and Azevedo, W.M.},
 doi = {10.1109/IJCNN.2012.6252601},
 booktitle = {Proceedings of the International Joint Conference on Neural Networks}
}

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