{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T21:42:36Z","timestamp":1780522956554,"version":"3.54.1"},"reference-count":15,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T00:00:00Z","timestamp":1558569600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004515","name":"Universiti Kebangsaan Malaysia","doi-asserted-by":"publisher","award":["GGPM-2017-009"],"award-info":[{"award-number":["GGPM-2017-009"]}],"id":[{"id":"10.13039\/501100004515","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2019,5,23]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.1155\/2019\/6252983","type":"journal-article","created":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T19:31:05Z","timestamp":1558639865000},"page":"1-10","source":"Crossref","is-referenced-by-count":11,"title":["Tropospheric Ozone Formation Estimation in Urban City, Bangi, Using Artificial Neural Network (ANN)"],"prefix":"10.1155","volume":"2019","author":[{"given":"Fatin Aqilah Binti","family":"Abdul Aziz","sequence":"first","affiliation":[{"name":"Chemical Engineering Programme, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norliza","family":"Abd. Rahman","sequence":"additional","affiliation":[{"name":"Chemical Engineering Programme, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia"},{"name":"Research Centre for Sustainable Process Technology, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4919-6131","authenticated-orcid":true,"given":"Jarinah","family":"Mohd Ali","sequence":"additional","affiliation":[{"name":"Chemical Engineering Programme, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia"},{"name":"Research Centre for Sustainable Process Technology, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","year":"2008"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1080\/15569543.2016.1225769"},{"issue":"11","key":"4","first-page":"90","year":"2003","journal-title":"Measure of Resources and the Environment"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/s0013-9351(02)00059-2"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1088\/1748-9326\/4\/4\/044014"},{"key":"8","volume":"5","year":"1991"},{"key":"9","year":"2005"},{"key":"10","year":"2005"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2004.02.002"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2014.08.060"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.03.023"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2018.02.062"},{"key":"16","first-page":"288","volume":"244","year":"2018","journal-title":"Environmental Pollution"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.14311\/nnw.2011.21.012"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemosphere.2018.02.111"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2019\/6252983.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2019\/6252983.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2019\/6252983.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T19:31:06Z","timestamp":1558639866000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cin\/2019\/6252983\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,23]]},"references-count":15,"alternative-id":["6252983","6252983"],"URL":"https:\/\/doi.org\/10.1155\/2019\/6252983","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,23]]}}}