Predicting Daily Ozone Concentration Maxima Using Fuzzy Time Series Based on Two-Stage Partition Method

Air pollution is associated with health effects,therefore air pollution is an important and popular topic. In Taiwan, the pollutant standard index (PSI) has been adopted to assess air pollution. The report of primary focus is for health,and the current PSI sub-indices reflect the PM 10 and O 4 measu...

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Bibliographic Details
Main Authors: Sue-Fen Huang, Ching-Hsue Cheng
Format: Conference Proceeding
Language:English
Subjects:
Air pollution
Atmospheric measurements
Current measurement
Educational technology
Fuzzy Time Series
Geoscience and remote sensing
Health information management
Humans
Management training
Predictive models
Probability distribution
Uniform Discretion Method
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Summary:Air pollution is associated with health effects,therefore air pollution is an important and popular topic. In Taiwan, the pollutant standard index (PSI) has been adopted to assess air pollution. The report of primary focus is for health,and the current PSI sub-indices reflect the PM 10 and O 4 measured concentrations. Therefore, this study uses O 3 attribute to evaluate air quality. This paper proposes a new fuzzy time series based on two-stage partition method to predict air quality by daily maximum O 3 concentration: (1) fuzzy time series based on uniform discretion method to partition the universe of discourse; (2) fuzzy time series based on cumulative probability distribution approach to partition the universe of discourse. The proposed methods are verified by practical collected dataset. From the results, the two proposed methods both outperform the listing methods in RMSE. The fuzzy time series methods can provide more accuracy predictions for the daily maxima ozone concentration.
DOI:10.1109/ETTandGRS.2008.388