Analysing livestock farm odour using an adaptive neuro-fuzzy approach

In this paper, a neuro-fuzzy-based method for analysing odour generation factors to the perception of livestock farm odour was proposed. The proposed approach incorporates neuro-adaptive learning techniques into fuzzy logic method. Rather than choosing the parameters associated with a given membership function by trail and error, these parameters could be tuned automatically in a systematic manner so as to adjust the membership functions of the input/output variables for optimal system performance. A multi-factor livestock farm odour model was developed, and both numeric factors and linguistic factors were considered. The proposed approach was tested with a livestock farm odour database. The results demonstrated the effectiveness of the proposed approach in comparison to a typical neural network model.