Developing a fuzzy model for Tehran's air quality
This research aims to offer a fuzzy approach for calculating Tehran's air pollution index. The method is based on fuzzy analysis model, and uses the information about air quality index (AQI), included on the website of Tehran’s Air Quality Monitoring And Supervision Bureau. The contrived fuzzy...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2015-01-01
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| Series: | Management Science Letters |
| Subjects: | |
| Online Access: | http://www.growingscience.com/msl/Vol5/msl_2014_325.pdf |
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| _version_ | 1849398046594433024 |
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| author | Nafiseh Tokhmehchi Ahmad Makui |
| author_facet | Nafiseh Tokhmehchi Ahmad Makui |
| author_sort | Nafiseh Tokhmehchi |
| collection | DOAJ |
| description | This research aims to offer a fuzzy approach for calculating Tehran's air pollution index. The method is based on fuzzy analysis model, and uses the information about air quality index (AQI), included on the website of Tehran’s Air Quality Monitoring And Supervision Bureau. The contrived fuzzy logic is considered a powerful tool for demonstrating the information associated with uncertainty. In the end, several graphs visualize this inferential system in various levels of pollution. |
| format | Article |
| id | doaj-art-a2a4b7fd5aac459ca143c5049b04d739 |
| institution | Kabale University |
| issn | 1923-2934 1923-9343 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | Management Science Letters |
| spelling | doaj-art-a2a4b7fd5aac459ca143c5049b04d7392025-08-20T03:38:44ZengGrowing ScienceManagement Science Letters1923-29341923-93432015-01-015110911610.5267/j.msl.2014.12.001Developing a fuzzy model for Tehran's air qualityNafiseh Tokhmehchi Ahmad MakuiThis research aims to offer a fuzzy approach for calculating Tehran's air pollution index. The method is based on fuzzy analysis model, and uses the information about air quality index (AQI), included on the website of Tehran’s Air Quality Monitoring And Supervision Bureau. The contrived fuzzy logic is considered a powerful tool for demonstrating the information associated with uncertainty. In the end, several graphs visualize this inferential system in various levels of pollution.http://www.growingscience.com/msl/Vol5/msl_2014_325.pdfAir pollutionAir Quality monitoringFuzzy logic |
| spellingShingle | Nafiseh Tokhmehchi Ahmad Makui Developing a fuzzy model for Tehran's air quality Management Science Letters Air pollution Air Quality monitoring Fuzzy logic |
| title | Developing a fuzzy model for Tehran's air quality |
| title_full | Developing a fuzzy model for Tehran's air quality |
| title_fullStr | Developing a fuzzy model for Tehran's air quality |
| title_full_unstemmed | Developing a fuzzy model for Tehran's air quality |
| title_short | Developing a fuzzy model for Tehran's air quality |
| title_sort | developing a fuzzy model for tehran s air quality |
| topic | Air pollution Air Quality monitoring Fuzzy logic |
| url | http://www.growingscience.com/msl/Vol5/msl_2014_325.pdf |
| work_keys_str_mv | AT nafisehtokhmehchi developingafuzzymodelfortehransairquality AT ahmadmakui developingafuzzymodelfortehransairquality |