@inbook{4a0738861e934b80912ca9ed413ebc98,
title = "Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data",
abstract = "For controlling air pollution, the Taiwan Environmental Protection Administration (TEPA) installed automatic air quality monitoring stations (AQMSs) and TEPA prescribed the industries to install continuous emission monitoring systems (CEMS). By 2014, there were a total of 76 AQMS and 351 CEMS in the entire nation. Therefore, the huge amount of air quality monitoring data forms big data. The processing, interpretation, collection and organization of air quality monitoring big data (AQMBD) have emerged in air quality control including industry management, traffic reduction, and residential health. In this chapter, the application of computational intelligence on analysis of air quality monitoring big data was reviewed worldwide. Additionally, the application of computational intelligence (CI) including artificial neural network, fuzzy theory, and adaptive network-based fuzzy inference system (ANFIS) was discussed. Finally, the implementation of CI on AQMBD granular computing was proposed.",
keywords = "Air quality monitoring big data, Artificial neural network, Computational intelligence, Swarm intelligence",
author = "Pai, {Tzu Yi} and Chang, {Moo Been} and Chen, {Shyh Wei}",
note = "Publisher Copyright: {\textcopyright} 2015, Springer International Publishing Switzerland.",
year = "2015",
doi = "10.1007/978-3-319-08254-7_21",
language = "???core.languages.en_GB???",
series = "Studies in Big Data",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "427--441",
booktitle = "Studies in Big Data",
}