The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models over particulate matter (PM10) variability during haze and non-haze episodes: A decade case study

The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models over particulate matter (PM10) variability during haze and non-haze episodes: A decade case study

The comprehensives of particulate matter studies are needed in predicting future haze occurrences in Malaysia. This paper presents the application of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) coupled with sensitivity analysis (SA) in order to recognize the pollutant rela...

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Bibliographic Details
Main Authors: Ku Yusof, Ku Mohd Kalkausar, Azid, Azman, Abdullah Sani, Muhamad Shirwan, Samsudin, Mohd Saiful, Muhammad Amin, Siti Noor Syuhada, Abd Rani, Nurul Latiffah, Jamalani, Mohd Asrul
Format: Article
Language:English
English
English
Published: Penerbit UTM Press 2019
Subjects:
QD Chemistry
Online Access:http://irep.iium.edu.my/71660/
http://irep.iium.edu.my/71660/9/71660_The%20evaluation%20on%20artificial%20neural%20networks%20%28ANN%29_mycite.pdf
http://irep.iium.edu.my/71660/15/71660_The%20evaluation%20on%20artificial%20neural%20networks%20%28ANN%29%20and%20multiple%20linear%20regressions%20%28MLR%29%20models%20over%20particulate%20matter%20%28PM10%29%20variability%20during%20haze%20and%20non-haze%20episodes_WOS.pdf
http://irep.iium.edu.my/71660/21/71660_The%20evaluation%20on%20artificial%20neural%20networks%20%28ANN%29.pdf

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