AIP Conference Proceedings, vol: 1746, (2016)
Web based prediction of pollutant PM10 concentration using Ruey Chyn Tsaur fuzzy time series model
Aripin A., Suryono S., Bayu S.
Abstract
Web-based predictions have an important role in economic, health and the environment issues. Prediction by using Fuzzy Time Series model has advantage in the use of historical data that classifies the set data into a blur limitation (fuzzy) compared to other conventional time series model which use data firm (crisp). As weather prediction that can give impact to humans, the prediction of pollutants PM10 concentration in the air also useful because the concentration of pollutant PM10 in the air is able to drive bad impact to humans. This research discusses about web-based prediction of PM10 pollutant concentration using Ruey Chyn Tsaur Fuzzy Time Series models. The pollutant PM10 concentrations data results obtained from the sensor will be sent to the web server and stored in an online database for further prediction using Fuzzy Time Series Ruey Chyn Tsaur models which implement re-divide the partition of interval after first partition of the universe of discourse. By using 30 data samples of pollutants PM10 concentrations in the prediction, we get the value of Mean Absolute Percentage Error (MAPE) is 0.0187%. It indicates that the Fuzzy Time Series Ruey Chyn Tsaur models is well proven to be used in predicting the pollutants PM10 concentration. © 2016 Author(s).
Keyword: Concentration of pollutants PM10; Ruey Chyn Tsaur Fuzzy Time Series models; Web based prediction