Development of fuzzy air quality index using soft computing approach.
Environ Monit Assess
; 184(10): 6187-96, 2012 Oct.
Article
en En
| MEDLINE
| ID: mdl-22083398
ABSTRACT
Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Monitoreo del Ambiente
/
Lógica Difusa
/
Contaminantes Atmosféricos
/
Contaminación del Aire
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Environ Monit Assess
Asunto de la revista:
SAUDE AMBIENTAL
Año:
2012
Tipo del documento:
Article
País de afiliación:
India