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Abolghasem Sadeghi‐Niaraki

Biographic Data

ID6878276
NAMEAbolghasem Sadeghi‐Niaraki
GIVEN NAMESAbolghasem
FAMILY NAMESadeghi‐Niaraki
SIGNATURENIARAKI A S
AFFILIATIONSSejong University
ORCID0000-0002-0048-8216
VERIFIEDYes
TOTAL WORKS9
TOTAL CITATIONS9
AUTHOR COUNT9
EDITOR COUNT0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Measuring Cognitive Load Index in Online Learning

    Open Access•Fatema Rahimi, Abolghasem Sadeghi-Niaraki et al.•ARTICLE•Journal of Computer Assisted…•2026

  • Spatio-temporal modeling of asthma-prone areas

    Open Access•Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•Sustainable Cities and Society•2024

  • People's olfactory perception potential mapping using a machine learning algorithm

    Open Access•Mahsa Farahani, Seyed Vahid Razavi-Termeh et al.•ARTICLE•Sustainable Cities and Society•2023

  • Ubiquitous GIS based outdoor evacuation assistance

    Open Access•Hamid Reza Ghafoori, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•International Journal of Disaster…•2022

  • A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment

    Open Access•Mahsa Farahani, Seyed Vahid Razavi-Termeh et al.•ARTICLE•Sustainable Cities and Society•2022

  • Covid-19 Risk Mapping with Considering Socio-Economic Criteria Using Machine Learning Algorithms

    Open Access•Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki et al.•ARTICLE•International Journal of…•2021

    The reduction of population concentration in some urban land uses is one way to prevent and reduce the spread of COVID-19 disease. Therefore, the objective of this study is to prepare the risk mapping of COVID-19 in Tehran, Iran, using machine learning algorithms according to socio-economic criteria of land use. Initially, a spatial database was created using 2282 locations of patients with COVID-19 from 2 February 2020 to 21 March 2020 and eight…

  • A volunteered geographic information system for monitoring and managing urban crimes

    Mohammadreza Jelokhani-Niaraki, Mohammadreza Jelokhani‐Niaraki et al.•ARTICLE•Police Practice and Research•2020

    Crime occurrence is an ever-increasing social problem of Tehran city. Crime management for this city requires social action, public participation or community-oriented policing. In this regard, Volunteered Geographic Information (VGI) systems can be of great support to community policing efforts. By employing such systems, members of the society can act as active, intelligent, responsible, location-aware, mobile, and distributed sensors in order …

  • A GIS-based decision support system for facilitating participatory urban renewal process

    Open Access•Morteza Omidipoor, Mohammadreza Jelokhani-Niaraki et al.•ARTICLE•Land Use Policy•2019•Cited by: 9•References: 51

  • A methodological framework for assessment of ubiquitous cities using ANP and Dematel methods

    Open Access•Tahere Ghaemi Rad, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•Sustainable Cities and Society•2018

    Smart and u-city is solution to exacerbating urban problems. • The main components and criteria of a smart and ubiquitous city are introduced. • A methodological framework for establishing and assessment of u-cities is developed. • Using ANP and DEMATEL methods to rank the importance of the criteria/components, the u-coefficients for Tehran and Seoul are calculated 0.449 and 0.918 respectively. • Tehran can be a smart city by enhancing its transp…

  • A GIS-based decision support system for facilitating participatory urban renewal process

    Open Access•Morteza Omidipoor, Mohammadreza Jelokhani-Niaraki et al.•ARTICLE•Land Use Policy•2019•Cited by: 9•References: 51

  • A methodological framework for assessment of ubiquitous cities using ANP and Dematel methods

    Open Access•Tahere Ghaemi Rad, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•Sustainable Cities and Society•2018

    Smart and u-city is solution to exacerbating urban problems. • The main components and criteria of a smart and ubiquitous city are introduced. • A methodological framework for establishing and assessment of u-cities is developed. • Using ANP and DEMATEL methods to rank the importance of the criteria/components, the u-coefficients for Tehran and Seoul are calculated 0.449 and 0.918 respectively. • Tehran can be a smart city by enhancing its transp…

  • A GIS-based decision support system for facilitating participatory urban renewal process

    Open Access•Morteza Omidipoor, Mohammadreza Jelokhani-Niaraki et al.•ARTICLE•Land Use Policy•2019•Cited by: 9•References: 51

  • A volunteered geographic information system for monitoring and managing urban crimes

    Mohammadreza Jelokhani-Niaraki, Mohammadreza Jelokhani‐Niaraki et al.•ARTICLE•Police Practice and Research•2020

    Crime occurrence is an ever-increasing social problem of Tehran city. Crime management for this city requires social action, public participation or community-oriented policing. In this regard, Volunteered Geographic Information (VGI) systems can be of great support to community policing efforts. By employing such systems, members of the society can act as active, intelligent, responsible, location-aware, mobile, and distributed sensors in order …

  • Covid-19 Risk Mapping with Considering Socio-Economic Criteria Using Machine Learning Algorithms

    Open Access•Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki et al.•ARTICLE•International Journal of…•2021

    The reduction of population concentration in some urban land uses is one way to prevent and reduce the spread of COVID-19 disease. Therefore, the objective of this study is to prepare the risk mapping of COVID-19 in Tehran, Iran, using machine learning algorithms according to socio-economic criteria of land use. Initially, a spatial database was created using 2282 locations of patients with COVID-19 from 2 February 2020 to 21 March 2020 and eight…

  • Ubiquitous GIS based outdoor evacuation assistance

    Open Access•Hamid Reza Ghafoori, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•International Journal of Disaster…•2022

  • A spatially based machine learning algorithm for potential mapping of the hearing senses in an urban environment

    Open Access•Mahsa Farahani, Seyed Vahid Razavi-Termeh et al.•ARTICLE•Sustainable Cities and Society•2022

  • People's olfactory perception potential mapping using a machine learning algorithm

    Open Access•Mahsa Farahani, Seyed Vahid Razavi-Termeh et al.•ARTICLE•Sustainable Cities and Society•2023

  • Spatio-temporal modeling of asthma-prone areas

    Open Access•Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki et al.•ARTICLE•Sustainable Cities and Society•2024

  • Measuring Cognitive Load Index in Online Learning

    Open Access•Fatema Rahimi, Abolghasem Sadeghi-Niaraki et al.•ARTICLE•Journal of Computer Assisted…•2026

Computer Science (8 works) · Geography (6 works) · Business (4 works) · Engineering (4 works) · Artificial Intelligence (3 works) · Computer security (3 works) · Environmental health (3 works) · Geographic information system (3 works) · Geographic Information Systems Studies (3 works) · Human Mobility and Location-Based Analysis (3 works)

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