Classification prediction of PM10 concentration using a tree-based machine learning approach

QR Code

Classification prediction of PM10 concentration using a tree-based machine learning approach

The PM10 prediction has received considerable attention due to its harmful effects on human health. Machine learning approaches have the potential to predict and classify future PM10 concentrations accurately. Therefore, in this study, three machine learning algorithms—namely, decision tree (DT), bo...

Full description

Bibliographic Details
Main Authors:	Wan Nur Shaziayani, Ul-Saufie, Ahmad Zia, Mutalib, Sofianita, Mohamad Noor, Norazian, Zainordin, Nazatul Syadia
Format:	Article
Published:	MDPI 2022
Online Access:	http://psasir.upm.edu.my/id/eprint/100704/

Similar Items

Pm10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
by: Japeri, Ahmad Zia Ul-Saufie Mohamad
Published: (2013)

PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
by: Mohamad Japeri, Ahmad Zia Ul-Saufie
Published: (2013)

Prediction Of PM10 Concentration Using Multiple Linear Regression And Support Vector Machine
by: Zailan, Masezatti
Published: (2018)

Prediction of pm10 concentration using multiple linear regression and support vector machine
by: Zailan, Masezatti
Published: (2018)

Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach
by: Hamid, Norfarhanah
Published: (2021)

Probabilistic And Distribution Modelling For Predicting Pm10 Concentration In Malaysia
by: Hamid, Hazrul Abdul
Published: (2013)

Analysis of pm10 using extreme value theory / Hasfazilah Ahmat ... [et al.]
by: Ahmat, Hasfazilah, et al.
Published: (2015)

Prediction Of PM10 Using Multiple Linear Regression And Boosted Regression Trees
by: Hamid, Nur Haziqah Mohd
Published: (2017)

Extreme value theory for modeling and prediction of high PM10 concentration in Johor
by: Mohd Amin, Nor Azrita, et al.
Published: (2013)

Modeling And Prediction Of Pm10 Concentration During High Particulate Events In Malaysia
by: Yusof, Noor Faizah Fitri Bt Md
Published: (2009)

Prediction Of Pm10 Concentrations Using Extreme Value Distributions (Evd) Classical And Bayesian Approaches
by: Ahmat, Hasfazilah
Published: (2016)

Association Between Walkability Index And Pedestrians’ Perspective In Reducing Exposure Of Schoolchildren To Ground Level Ozone
by: Zainordin, Nazatul Syadia
Published: (2017)

Short-Term Prediction Models Of Pm10 Concentrations In Peninsular Malaysia Using Multivariate Time Series And Machine Learning Methods
by: Ramli, Norazrin
Published: (2021)

Prediction Of PM10 Concentration Using Multiple Linear Regression And Bayesian Model Averaging
by: Ismail, Hafizahizzati
Published: (2017)

Pedestrians perspectives on environmental problems, awareness and willingness in changing current mode to walking in a possible way to reduce exposure of o3 concentrations to school children
by: Zainordin, Nazatul Syadia, et al.
Published: (2018)

Imputing missing values in modelling the PM10 concentrations
by: Nuradhiathy Abd Razak,, et al.
Published: (2014)

Modeling Locational Differences And Prediction Of Temporal Concentration Of Pm10 Using Time Series Analysis
by: Sansuddin, Nurulilyana
Published: (2010)

Bayesian extreme for modeling high PM10 concentration in Johor
by: Mohd Amin, Nor Azrita, et al.
Published: (2015)

Bivariate extreme value with application to PM10 concentration analysis
by: Mohd Amin, Nor Azrita, et al.
Published: (2014)

Statistical Modelling For Forecasting Pm10 Concentrations In Peninsular Malaysia
by: Ng, Kar Yong
Published: (2017)

Diurval Variation Of PM10 And Carbon Monoxide Concentrations In Penang
by: Abd. Manaff, Liana Syafinaz
Published: (2005)

An investigation of PM10 concentrations at one site of Kuala Lumpur
by: Mohd. Yusoff, Mohd. Rashid
Published: (1987)

Investigation into the effect of atmospheric particulate matter (PM2.5 and PM10) concentrations on GPS signals
by: Lau, Lawrence, et al.
Published: (2017)

Future Daily PM10 Concentrations Prediction In Malaysia Using Artificial Neural Networks, Stochastic Regression And Hybrid Models
by: Yahaya, Ahmad Shukri, et al.
Published: (2015)

Time series analysis of PM10 concentration in Parit Raja residential area
by: Raffee, Ahmad Fauzi, et al.
Published: (2018)

Indoor Concentrations of PM10 and Factors Influencing Its Concentrations in Day Care Centres in Bangkok, Thailand
by: Pudpong, N., et al.
Published: (2011)

Characteristics of airborne Pm2.5 and Pm2.5-10 in the urban environment of Kuala Lumpur
by: Yusuf, Sara Yasina, et al.
Published: (2013)

Inorganic PM10 emission from the combustion of individual mallee components and whole-tree biomass
by: Gao, Xiangpeng, et al.
Published: (2017)

SMOTE-PCADBSCAN: a novel approach for addressing class imbalance in water quality prediction
by: Norashikin Nasaruddin,, et al.
Published: (2025)

Air quality in library: assessment of pm10 and pm2.5 concentrations at different floor levels of USM Health Campus’s Library
by: Nordin, Siti Mariam
Published: (2016)

The role of regional atmospheric stability in high-pm10 concentration episodes in Miercurea Ciuc (Harghita)
by: Szép, R., et al.
Published: (2014)

Concentration and composition of PM10 in outdoor and indoor air in industrial area of Balakong Selangor , Malaysia
by: Norela Sulaiman,, et al.
Published: (2005)

A study on the concentration and dispersion of PM10 in UTHM by using simple modelling and meteorological factors
by: Abd Rahman, Malek Faizal
Published: (2013)

PM : Concentrate on bio-safety
Published: (2008)

Phylogenetic tree classification system using machine learning algorithm
by: Tan, Jia Kae
Published: (2015)

Can we predict atmospheric PM2.5 concentration more accurately?
by: Jian, Le, et al.
Published: (2012)

Does light pollution affect nighttime ground-level ozone concentrations?
by: Shith, Syabiha, et al.
Published: (2022)

PM10 Retrieval From Spectroradiometer Measurements.
by: H, S Lim, et al.
Published: (2005)

Distribution and temporal behaviour of O3 and NO2 near selected schools in Seberang Perai, Pulau Pinang and Parit Buntar, Perak, Malaysia
by: Nazatul Syadia Zainordin,, et al.
Published: (2017)

Classification of stock market index based on predictive fuzzy decision tree
by: Khokhar, Arashid Hafeez
Published: (2005)