The objective of designing and installation air quality monitoring network (AQMN) is to reduce network density with a view to acquire maximum information on air quality with minimum expenses. In spite of the best research efforts, there has been no general acceptance of any method for deciding the number of stations. Majority of the cities have, therefore, installed monitoring stations with their own guidelines. The present paper presents a useful formulation for classification of the existing air quality monitoring stations (AQMS) using fuzzy similarity measures. The case study has been demonstrated by applying the methodology to the already-installed AQMS in Delhi, India.
|Title of host publication||Recent Developments and New Direction in Soft-Computing Foundations and Applications|
|Subtitle of host publication||Selected Papers from the 4th World Conference on Soft Computing, May 25-27, 2014, Berkeley|
|Editors||Lotfi A. Zadeh, Ali M. Abbasov, Ronald R. Yager, Shahnaz N. Shahbazova, Marek Z. Reformat|
|Place of Publication||Switzerland|
|Number of pages||13|
|Publication status||Published - 2016|
|Name||Studies in Fuzziness and Soft Computing|