Knowledge-based air quality management study by Fuzzy Logic principle

The object of this study is to derive a knowledge-based air quality management system by fuzzy logic concept. An evaluation system of air quality management knowledge base was established in this study. The external environmental costs caused by air pollution were studied using the fuzzy theory. The...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 5; pp. 3064 - 3069
Main Authors Dong-Liang Cai, Wang-Kun Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Air pollution
Air quality management
Atmospheric measurements
Control strategy
Costs
Decision making
Fuzzy control
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Pollution measurement
Quality management
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Summary:The object of this study is to derive a knowledge-based air quality management system by fuzzy logic concept. An evaluation system of air quality management knowledge base was established in this study. The external environmental costs caused by air pollution were studied using the fuzzy theory. The so-called ldquofuzzy decision index, FDIrdquo was derived and applied in this research. An integrated score of multiple assessments was derived by fuzzy logic in this study. The so-called ldquofuzzy decision index, FDIrdquo was derived and applied in this research. The knowledge database established in this study include: emission source, meteorology, topography, and population density distribution. The external costs of air pollutants calculated in this study can provide the government a good reference on air pollution decision making, such as the air pollution control fee, and let the public people have a closer understanding for the regional air quality conditions of their own region.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212610