Title :
Knowledge-based air quality management study by Fuzzy Logic principle
Author :
Cai, Dong-liang ; Chen, Wang-Kun
Author_Institution :
Dept. of Inf. Eng., Jinwen Univ. of Sci. & Technol., Taipei, Taiwan
Abstract :
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.
Keywords :
air pollution control; decision making; decision theory; environmental management; fuzzy control; fuzzy set theory; knowledge based systems; statistical distributions; air pollution control fee; decision making; emission source; external environmental cost; fuzzy decision index; fuzzy logic principle; fuzzy set theory; knowledge-based air quality management system; meteorology; population density distribution; topography; Air pollution; Atmospheric measurements; Costs; Decision making; Fuzzy control; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Pollution measurement; Quality management; Air quality management; Control strategy; Fuzzy Logic;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212610