1 resultado para self-organizing map
em eResearch Archive - Queensland Department of Agriculture
Filtro por publicador
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (3)
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- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (4)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (4)
- Aston University Research Archive (28)
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- Universitat de Girona, Spain (2)
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- University of Queensland eSpace - Australia (3)
Resumo:
Identification of major contributors to odour annoyance in areas with multiple emission sources is necessary to address and resolve odour disputes. In an effort to develop an appropriate tool for this task, odour samples were collected on-site at a piggery and an abattoir (the major odour sources in the area) and at surrounding off-site areas, then analysed using a commercial non-specific chemical sensor array to develop an odour fingerprint database. The developed odour fingerprint database was analysed using two pattern recognition algorithms including a partial least squares-discriminant analysis (PLS-DA) and a Kohonen self-organising map (KSOM). The KSOM model could identify odour samples sourced from the piggery shed 15, piggery pond 8, piggery pond 9, abattoir, motel and others with mean percentage values of 77.5, 65.0, 90.2, 75.7, 44.8 and 64.6%, respectively.