Analysis of air quality index (AQI) in Klang valley using artificial neural network (ANN) technique / Rosli Idris
This project investigates and analyzes the effectiveness of Artificial Neural Networks (ANN) technique in predicting the Air Quality Index (AQI) in Klang Valley. The ANN technique simplifies and speeds up the computation of the AQI, as compared to the current existing method used by Department of En...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2007
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/102674/1/102674.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This project investigates and analyzes the effectiveness of Artificial Neural Networks (ANN) technique in predicting the Air Quality Index (AQI) in Klang Valley. The ANN technique simplifies and speeds up the computation of the AQI, as compared to the current existing method used by Department of Environment (DOE). In the ANN technique, three methods will be used. The methods are Levenberg-Marquardt Algorithms, Resilient Backpropagation and Quasi-Newton Algorithms will be considered adopted to analyze the AQI data. Between these three methods, the Levenberg-Marquardt Algorithms is the best method for analyzing AQI data with the lowest error of data during training process which is from -0.5569 to 0.5787 and also has the fastest learning or training the AQI data. |
|---|