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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Application of Machine Learning for Modelling Concentration and Dispersal of Air Pollutants in Alesa-Eleme, Rivers State Nigeria. |
| Authors Name: | Ahmad, Kabiru , Leton, T. G , Ugbebor, J. N |
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IJNRD_204174
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| Published Paper Id: | IJNRD2308335 |
| Published In: | Volume 8 Issue 8, August-2023 |
| DOI: | |
| Abstract: | This research was conducted to explore the use of machine learning approach in modeling the relationship between air pollutants (CO2, VOC, PM10,) and meteorological parameters (Wind Speed, Air temperature, Solar Radiation) in Alesa-Eleme, River State. The data was gathered using AQM 65 at three (3) sites spread over the study area for a period of fourteen (14) Months. Statistical analysis of the data reveled the relationship between air pollutants concentrations and meteorological parameters. The correlated parameters were subjected to Machine Learning (ML) techniques; RF, NB, ANN, SVM and LR to predict concentration and dispersal of air pollutants in relation to meteorological dynamics. The five ML technique were evaluated and validated, and the result showed that RF was more accurate than the other considered ML techniques, and therefore was used in the prediction of pollutants concentration and dispersal using Orange Canvas and WEKA software. Applying the RF, pollutants concentrations were estimated with CA of 0.874 and Precision of 0.881. This implies that the application of ML concept using high quality and accurate data can bring more advances in Nigeria not only for air quality prediction, but any type of environmental monitoring to help preparedness, raise awareness and build resilient Environmental Management System, especially in areas more prone to industrial pollution. |
| Keywords: | Air pollutants, Meteorological Parameters, Machine Learning, Modelling, Dispersal, Prediction. |
| Cite Article: | "Application of Machine Learning for Modelling Concentration and Dispersal of Air Pollutants in Alesa-Eleme, Rivers State Nigeria.", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 8, page no.d152-d168, August-2023, Available :http://www.ijnrd.org/papers/IJNRD2308335.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2308335 Registration ID: 204174 Published In: Volume 8 Issue 8, August-2023 DOI (Digital Object Identifier): Page No: d152-d168 Country: University of Port Harcourt, Rivers State, Nigeria Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2308335 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2308335 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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