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State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

Author

Listed:
  • Saeed Nosratabadi
  • Amir Mosavi
  • Ramin Keivani
  • Sina Ardabili
  • Farshid Aram

Abstract

Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis of smart cities and urban development. This paper presents the state of the art of DL and ML methods used in this realm. Through a novel taxonomy, the advances in model development and new application domains in urban sustainability and smart cities are presented. Findings reveal that five DL and ML methods have been most applied to address the different aspects of smart cities. These are artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, and neuro-fuzzy; and deep learning. It is also disclosed that energy, health, and urban transport are the main domains of smart cities that DL and ML methods contributed in to address their problems.

Suggested Citation

  • Saeed Nosratabadi & Amir Mosavi & Ramin Keivani & Sina Ardabili & Farshid Aram, 2020. "State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability," Papers 2010.02670, arXiv.org.
    • Handle: RePEc:arx:papers:2010.02670
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    References listed on IDEAS

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    1. Majid Dehghani & Hossein Riahi-Madvar & Farhad Hooshyaripor & Amir Mosavi & Shahaboddin Shamshirband & Edmundas Kazimieras Zavadskas & Kwok-wing Chau, 2019. "Prediction of Hydropower Generation Using Grey Wolf Optimization Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 12(2), pages 1-20, January.
    2. Izabela Rojek & Jan Studzinski, 2019. "Detection and Localization of Water Leaks in Water Nets Supported by an ICT System with Artificial Intelligence Methods as a Way Forward for Smart Cities," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    3. Farshid Aram & Ebrahim Solgi & Ester Higueras García & Danial Mohammadzadeh S. & Amir Mosavi & Shahaboddin Shamshirband, 2019. "Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    4. Yongtao Tan & Chenyang Shuai & Liudan Jiao & Liyin Shen, 2018. "Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study," Sustainable Development, John Wiley & Sons, Ltd., vol. 26(6), pages 749-764, November.
    5. Kwok Tai Chui & Miltiadis D. Lytras & Anna Visvizi, 2018. "Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption," Energies, MDPI, vol. 11(11), pages 1-20, October.
    6. Ju, Jingrui & Liu, Luning & Feng, Yuqiang, 2018. "Citizen-centered big data analysis-driven governance intelligence framework for smart cities," Telecommunications Policy, Elsevier, vol. 42(10), pages 881-896.
    7. Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
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    Cited by:

    1. Malinka Ivanova & Mariana Durcheva, 2023. "M-Polar Fuzzy Graphs and Deep Learning for the Design of Analog Amplifiers," Mathematics, MDPI, vol. 11(4), pages 1-16, February.
    2. Min Zhang & Yufu Liu & Yixiong Xiao & Wenqi Sun & Chen Zhang & Yong Wang & Yuqi Bai, 2021. "Vulnerability and Resilience of Urban Traffic to Precipitation in China," IJERPH, MDPI, vol. 18(23), pages 1-13, November.
    3. Saeed Nosratabadi & Gergo Pinter & Amir Mosavi & Sandor Semperger, 2020. "Sustainable Banking; Evaluation of the European Business Models," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    4. Jiaxin Zhang & Zhilin Yu & Yunqin Li & Xueqiang Wang, 2023. "Uncovering Bias in Objective Mapping and Subjective Perception of Urban Building Functionality: A Machine Learning Approach to Urban Spatial Perception," Land, MDPI, vol. 12(7), pages 1-20, June.
    5. Saeed Nosratabadi & Gergo Pinter & Amir Mosavi & Sandor Semperger, 2020. "Sustainable Banking; Evaluation of the European Business Models," Papers 2003.13423, arXiv.org.

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