Abstract
Each stage of the sewage treatment process emits odor causing compounds and these compounds may vary from one location in a sewage treatment works to another. In order to determine the boundaries of legal standards, reliable and efficient odor measurement methods need to be defined. An electronic NOSE equipped with 12 different polypyrrole sensors is used for the purpose of characterizing sewage odors. Samples collected at different locations of a WWTP were classified using a fuzzy clustering technique and a neural network trained with a back-propagation algorithm.
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© 2005 Springer-Verlag Berlin Heidelberg
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Önkal-Engin, G., Demir, I., Engin, S.N. (2005). e-NOSE Response Classification of Sewage Odors by Neural Networks and Fuzzy Clustering. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_92
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DOI: https://doi.org/10.1007/11539117_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
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