Noise Annoyance Modelling using Fuzzy Rule Based Systems

This paper presents a model that uses a fuzzy rule based engine to predict noise annoyance reported by individuals in a social survey. The rules are proposed by the human expert and are based on linguistic variables. The approach then adapts the sufficiency degree or certainty of a rule to tune the model to a particular survey. Although all possible relations between exposure, attitudinal, emotional, personal, environmental and social variables are not included in the model as yet, the benefits of the new approach are clearly demonstrated. A major limitation that remains is the varying theoretical and empirical basis of the expert for different subset of annoyance determinants. Future applications may include more accurate predictions of noise annoyance for policy support and extraction of knowledge concerning the construct of annoyance from surveys.