Smart Cities-Based Improving Atmospheric Particulate Matters Prediction Using Chi-Square Feature Selection Methods by Employing Machine Learning Techniques

Hanan Abdullah Mengasha Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Lal Hussainb Department of Computer Science and Information Technology, King Abdullah Campus, University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan;c Department of Computer Science & IT, Neelum Campus, University of Azad Jammu and Kashmir Athmuqam, Azad Kashmir, PakistanCorrespondence[email protected]

https://orcid.org/0000-0003-1103-4938

Hany Mahgoubd Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Abha, Saudi Arabia;e Faculty of Computers and Information, Computer Science Department, Menoufia University, Menofia Governorat, Egypt

A. Al-Qarafif College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

Mohamed K Nourg Department of Computer Sciences, College of Computing and Information System, Umm Al-Qura University, Mecca, Saudi Arabia

Radwa Marzouka Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Shahzad Ahmad Qureshih Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan

Anwer Mustafa Hilali Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam Bin Abdulaziz University, AlKharj, Saudi Arabia

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Smart Cities-Based Improving Atmospheric Particulate Matters Prediction Using Chi-Square Feature Selection Methods by Employing Machine Learning Techniques

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Smart Cities-Based Improving Atmospheric Particulate Matters Prediction Using Chi-Square Feature Selection Methods by Employing Machine Learning Techniques

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