Soft-computing base analyses of the relationship between annoyance and coping with noise and odor.

The majority of research on annoyance as an important impact of noise, odor, and other stressors on man, has regarded the person as a passive receptor. It was however recognized that this person is an active participant trying to alter a troubled person-environment relationship or to sustain a desirable one. Coping has to be incorporated. This is of particular importance in changing exposure situations. For large populations a lot of insight can be gained by looking at average effects only. To investigate changes in annoyance and effects of coping, the individual or small group has to be studied. Then it becomes imperative to recognize the inherent vagueness in perception and human behavior. Fortunately, tools have been developed over the past decades that allow doing this in a mathematically precise way. These tools are sometimes referred to by the common label: soft-computing, hence the title of this paper. This work revealed different styles of coping both by blind clustering and by (fuzzy) logical aggregation of different actions reported in a survey. The relationship between annoyance and the intensity of coping it generates was quantified after it was recognized that the possibility for coping is created by the presence of the stressor rather than the actual fact of coping. It was further proven that refinement of this relationship is possible if a person can be identified as a coper. This personal factor can be extracted from a known reaction to one stressor and be used for predicting coping intensity and style in another situation. The effect of coping on a perceived change in annoyance is quantified by a set of fuzzy linguistic rules. This closes the loop that is responsible for at least some of the dynamics of the response to a stressor. This work thus provides all essential building blocks for designing models for annoyance in changing environments.