Pollution modelling for Hong Kong downtown area using principal component analysis and artificial neural networks

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

4 Scopus Citations
View graph of relations

Author(s)

  • H. Y. Fan
  • A. Y T Leung
  • W. J. Wang
  • J. C K Wong

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering
Pages59-60
Publication statusPublished - 2001

Conference

TitleProceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering
PlaceAustria
CityVienna
Period19 - 21 September 2001

Abstract

A study was performed on pollution modelling for Hong Kong downtown area using principal component analysis and artificial neural networks. The hourly local concentration of nitric oxide, nitrogen dioxide, nitrogen oxides, carbon monoxide, sulphur dioxide and respirable suspended particles were recorded. It was found that established neural networks had a good ability to forecast the concentration of RSP.

Research Area(s)

  • Environmental, Modelling, Neural network, Pollutant, Principal component analysis, Respirable suspended particulate

Citation Format(s)

Pollution modelling for Hong Kong downtown area using principal component analysis and artificial neural networks. / Lu, W. Z.; Fan, H. Y.; Leung, A. Y T et al.
Proceedings of the Sixth International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering. 2001. p. 59-60.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review