Tropospheric ozone formation estimation in Urban City, Bangi, Using Artificial Neural Network (ANN)

Fatin Aqilah Binti Abdul Aziz, Norliza Abd Rahman, Jarinah Mohd Ali

Research output: Contribution to journalArticle

Abstract

Due to the rapid development of economy and society around the world, the most urban city is experiencing tropospheric ozone or commonly known as ground-level air pollutants. The concentration of air pollutants must be identified as an early precaution step by the local environmental or health agencies. This work aims to apply the artificial neural network (ANN) in estimating the ozone concentration forecast in Bangi. It consists of input variables such as temperature, relative humidity, concentration of nitrogen dioxide, time, UVA and UVB rays obtained from routine monitoring, and data recorded. Ten hidden layer is utilized to obtain the optimized ozone concentration, which is the output layer of the ANN framework. The finding showed that the meteorology condition and emission patterns play an important part in influencing the ozone concentration. However, a single network is sufficient enough to estimate the concentration despite any circumstances. Thus, it can be concluded that ANN is able to give reliable and satisfactory estimations of ozone concentration for the following day.

Original languageEnglish
Article number6252983
JournalComputational Intelligence and Neuroscience
Volume2019
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint

Ozone
Artificial Neural Network
Neural networks
Air Pollutants
Pollutants
Meteorology
Nitrogen Dioxide
Environmental Health
Air
Humidity
Relative Humidity
Atmospheric humidity
Health
Nitrogen
Forecast
Half line
Temperature
Monitoring
Sufficient
Output

ASJC Scopus subject areas

  • Computer Science(all)
  • Neuroscience(all)
  • Mathematics(all)

Cite this

Tropospheric ozone formation estimation in Urban City, Bangi, Using Artificial Neural Network (ANN). / Abdul Aziz, Fatin Aqilah Binti; Abd Rahman, Norliza; Mohd Ali, Jarinah.

In: Computational Intelligence and Neuroscience, Vol. 2019, 6252983, 01.01.2019.

Research output: Contribution to journalArticle

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