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Mohammad Khishe ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Wang, Qiong / Chen, Gang / Khishe, Mohammad / Ibrahim, Banar Fareed / Rashidi, Shima (2023): Multi-objective optimization of IoT-based green building energy system using binary metaheuristic algorithms. In: Journal of Building Engineering, v. 68 (Juni 2023).

    https://doi.org/10.1016/j.jobe.2023.106031

  2. Mahmoodzadeh, Arsalan / Nejati, Hamid Reza / Mohammadi, Mokhtar / Hashim Ibrahim, Hawkar / Khishe, Mohammad / Rashidi, Shima / Hussein Mohammed, Adil (2022): Developing six hybrid machine learning models based on gaussian process regression and meta-heuristic optimization algorithms for prediction of duration and cost of road tunnels construction. In: Tunnelling and Underground Space Technology, v. 130 (Dezember 2022).

    https://doi.org/10.1016/j.tust.2022.104759

  3. Wang, Le / Khishe, Mohammad / Mohammadi, Mokhtar / Mahmoodzadeh, Arsalan (2022): Extreme learning machine evolved by fuzzified hunger games search for energy and individual thermal comfort optimization. In: Journal of Building Engineering, v. 60 (November 2022).

    https://doi.org/10.1016/j.jobe.2022.105187

  4. Mahmoodzadeh, Arsalan / Mohammadi, Mokhtar / Hashim Ibrahim, Hawkar / Nariman Abdulhamid, Sazan / Farid Hama Ali, Hunar / Mohammed Hasan, Ahmed / Khishe, Mohammad / Mahmud, Hoger (2021): Machine learning forecasting models of disc cutters life of tunnel boring machine. In: Automation in Construction, v. 128 (August 2021).

    https://doi.org/10.1016/j.autcon.2021.103779

  5. Mahmoodzadeh, Arsalan / Mohammadi, Mokhtar / M Gharrib Noori, Krikar / Khishe, Mohammad / Hashim Ibrahim, Hawkar / Farid Hama Ali, Hunar / Nariman Abdulhamid, Sazan (2021): Presenting the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques. In: Automation in Construction, v. 127 (Juli 2021).

    https://doi.org/10.1016/j.autcon.2021.103719

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