Feature Selection Methods Using RBFNN Based on Enhance Air Quality Prediction: Insights from Shah Alam

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Feature Selection Methods Using RBFNN Based on Enhance Air Quality Prediction: Insights from Shah Alam

This study examines the predictive efficiency of several feature selection approaches in air quality models aimed to predict next-day PM2.5 concentrations in Shah Alam, Malaysia. Air pollution in urban areas is a significant public health concern, and accurate prediction models are essential for tim...

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Bibliographic Details
Published in:	INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
Main Authors:	Arafin, Siti Khadijah; Ul-Saufie, Ahmad Zia; Ghani, Nor Azura Md; Ibrahim, Nurain
Format:	Article
Language:	English
Published:	SCIENCE & INFORMATION SAI ORGANIZATION LTD 2024
Subjects:	Computer Science
Online Access:	https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-recordWOS:001378221800001

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