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An electronic nose system for monitoring the quality of potable water

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UNSPECIFIED (2000) An electronic nose system for monitoring the quality of potable water. In: 6th International Symposium on Electronic Noses (ISOEN 99), SEP 20-22, 1999, TUBINGEN, GERMANY.

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Abstract

A measurement system has been developed for the testing of cyanobacteria in water, and it consists of three main stages: the odour sampling system, an electronic nose (e-nose) and a CellFacts instrument that analyses liquid samples. The e-nose system, which employs an array of six commercial odour sensors, has been used to monitor not only different strains but also the growth phase of cyanobacteria (i.e. blue-green algae) in water over a 40-day period. Principal components analysis (PCA), multi-layer perceptron (MLP), learning vector quantisation (LVQ) and Fuzzy ARTMAP were used to analyse the response of the sensors. The optimal MLP network was found to classify correctly 97.1% of the unknown nontoxic and 100% of the unknown toxic cyanobacteria. The optimal LVQ and Fuzzy ARTMAP algorithms were able to classify 100% of both strains of cyanobacteria samples. The accuracy of MLP, LVQ and Fuzzy ARTMAP in terms of predicting four different growth phases of toxic cyanobacteria was 92.3%, 95.1% and 92.3%, respectively. These results show the potential application of neural network based e-noses to test the quality of potable water as an alternative to instruments, such as liquid chromatography or optical microscopy. (C) 2000 Elsevier Science S.A. All rights reserved.

Item Type: Conference Item (UNSPECIFIED)
Subjects: Q Science > QD Chemistry
Journal or Publication Title: SENSORS AND ACTUATORS B-CHEMICAL
Publisher: ELSEVIER SCIENCE SA
ISSN: 0925-4005
Date: 25 October 2000
Volume: 69
Number: 3
Number of Pages: 6
Page Range: pp. 336-341
Publication Status: Published
Title of Event: 6th International Symposium on Electronic Noses (ISOEN 99)
Location of Event: TUBINGEN, GERMANY
Date(s) of Event: SEP 20-22, 1999
URI: http://wrap.warwick.ac.uk/id/eprint/12842

Data sourced from Thomson Reuters' Web of Knowledge

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