Analyzing Livestock Farm Odour Using a Neuro-fuzzy Approach
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.
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