Scaling of railway noise annoyance based on fuzzy theory

在日本和其他国家的社会调查中，已经使用了各种各样的量表来调查社区对环境噪声的反应。这使得很难在调查之间直接比较烦恼响应数据。为探讨不同烦恼度引起的社区反应差异，采用4种烦恼度量表（4 ~ 7分）进行铁路噪声社区反应社会调查。向统一的答复者群体分发了调查表。比较了不同尺度下噪声暴露与反应的关系。被证明的比率，如%非常恼火的是强烈影响的词分配给categoty略低于范围的烦恼。本文基于模糊理论，探讨了不同烦恼度等级下铁路噪声社区反应的评价方法，并通过对不同烦恼度等级下铁路噪声的言语描述，发现了不同形容词短语和不同副词所标注的类别群模糊集之间的相互关系烦恼。

Various kinds of scales have been used in social surveys on community response to environmental noise in Japan and other countries. This makes it difficult to compare annoyance response data directly between the surveys. To discuss the difference in community response due to different annoyance scales, a social survey on community response to railway noise was carried out by using four kinds of questionnaire with 4-to 7-point annoyance scales. Questionnaires were distributed to the unified groups of respondents. The relationships between noise exposure and response were compared between different scales. The rate such as % very annoyed was proven to be strongly affected by the word assigned to the categoty just below the range of annoyance. This shows that the descriptors assigned to each category are very important in comparing the results obtained from different surveys.Based on the fuzzy theory we discussed a new evaluation method for community response to the railway noise with different annoyance scales and found the mutual relationship among fuzzy sets of the category group which were labeled by different adjective phrases with different adverbs for the verbal description representing the level of annoyance.