A Fast PM2.5 Forecast Approach Based on Time-Series Data Analysis, Regression and Regularization

Cyuan Heng Luo, Hsuan Yang, Li Pang Huang, Sachit Mahajan, Ling Jyh Chen

研究成果: 書貢獻/報告類型會議論文篇章

6 引文 斯高帕斯(Scopus)

摘要

The problem of air pollution has become a serious issue in developed as well as developing countries. Unfortunately, most of the current solutions are not very effective and this makes it important to have an efficient early warning system for monitoring and forecasting air quality. Our main focus is to build a real-time forecasting system with high accuracy, and deploy it in Taiwan. In this paper, we propose a forecast method called Adaptive Iterative Forecast (AIF), which can predict the value of PM2.5 for the next few hours (by linear programming, normalization and time-series) based on the trend of historical data. The goal of this research is to develop an efficient and accurate forecast model. Through various comparative analyses, we have proved that our model can achieve significant results. Based on the results, we have also built a real-time forecasting system which allows the users to stay aware of the air quality and plan their day to day life.

原文英語
主出版物標題Proceedings - 2018 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2018
發行者Institute of Electrical and Electronics Engineers Inc.
頁面78-81
頁數4
ISBN(電子)9781728112299
DOIs
出版狀態已發佈 - 2018 十二月 24
事件2018 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2018 - Taichung, 臺灣
持續時間: 2018 十一月 302018 十二月 2

出版系列

名字Proceedings - 2018 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2018

會議

會議2018 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2018
國家臺灣
城市Taichung
期間2018/11/302018/12/02

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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