Principal Component Regression and Artificial Neural Network: The Prediction of Air Pollution Index (API)
,
Abstract
None
1. McAdams HT, Crawford RW, Hadder GR (2000). A vector approach to regression analysis and its application to heavy-duty diesel emissions. Society of Automotive Engineers, Inc, Contract with the Energy Division of Oak Ridge National Labora-tory (ORNL). Contract No. DE-AC05-00OR22725.
2. Lengyel A, Héberger K, Paksy L, Bánhidi O, Rajkó R (2004). Prediction of ozone con-centration in ambient air using multivari-ate methods. Chemosphere, 57(8): 889-896.
3. Klaus D, Poth A, Voss M, Jáuregui E (2001). Ozone distributions in Mexico City using principal component analysis and its relation to meteorological parame-ters. Atmosfera, 14(4): 171-188.
4. Rahman NHA, Lee MH, Latif MT (2013). Forecasting of air pollution index with ar-tificial neural network. JurnalTeknologi (Sci-ences and Engineering), 63(2): 59-64.
2. Lengyel A, Héberger K, Paksy L, Bánhidi O, Rajkó R (2004). Prediction of ozone con-centration in ambient air using multivari-ate methods. Chemosphere, 57(8): 889-896.
3. Klaus D, Poth A, Voss M, Jáuregui E (2001). Ozone distributions in Mexico City using principal component analysis and its relation to meteorological parame-ters. Atmosfera, 14(4): 171-188.
4. Rahman NHA, Lee MH, Latif MT (2013). Forecasting of air pollution index with ar-tificial neural network. JurnalTeknologi (Sci-ences and Engineering), 63(2): 59-64.
| Files | ||
| Issue | Vol 50 No 7 (2021) | |
| Section | Letter to the Editor | |
| DOI | https://doi.org/10.18502/ijph.v50i7.6645 | |
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Hua A, Gani P. Principal Component Regression and Artificial Neural Network: The Prediction of Air Pollution Index (API). Iran J Public Health. 2021;50(7):1493-1494.
