Analyzing livestock farm odour using a neuro-fuzzy approach

Authors:
Leilei Pan;Simon X. Yang
Affiliations:
School of Engineering, University of Guelph, Guelph, ON, Canada;School of Engineering, University of Guelph, Guelph, ON, Canada
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
Year:
2006

Citing 3
Cited 0

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Abstract

An adaptive neuro-fuzzy based method for analyzing odour generation factors to the perception of livestock farm odour was proposed. In this approach, the parameters associated with a given membership function could be tuned so as to tailor the membership functions to the input/output data in order to account for these types of variations in the data values. A multi-factor livestock farm odour model was developed, and both numeric factors and linguistic factors were considered. The proposed method was tested with a livestock farm odour database. The results demonstrated the effectiveness of the proposed approach in comparison to a typical neural network.