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Hossein Moayedi

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

  1. Moayedi, Hossein / Hayati, Sajad (2018): Applicability of a CPT-Based Neural Network Solution in Predicting Load-Settlement Responses of Bored Pile. In: International Journal of Geomechanics, v. 18, n. 6 (Juni 2018).

    https://doi.org/10.1061/(asce)gm.1943-5622.0001125

  2. Nazir, Ramli / Moayedi, Hossein / Mosallanezhad, Mansour / Tourtiz, Alireza (2015): Appraisal of reliable skin friction variation in a bored pile. In: Proceedings of the Institution of Civil Engineers - Geotechnical Engineering, v. 168, n. 1 (Februar 2015).

    https://doi.org/10.1680/geng.13.00140

  3. Qiao, Weibiao / Moayedi, Hossein / Foong, Loke Kok (2020): Nature-inspired hybrid techniques of IWO, DA, ES, GA, and ICA, validated through a k-fold validation process predicting monthly natural gas consumption. In: Energy and Buildings, v. 217 (Juni 2020).

    https://doi.org/10.1016/j.enbuild.2020.110023

  4. Guo, Zhanjun / Moayedi, Hossein / Foong, Loke Kok / Bahiraei, Mehdi (2020): Optimal modification of heating, ventilation, and air conditioning system performances in residential buildings using the integration of metaheuristic optimization and neural computing. In: Energy and Buildings, v. 214 (Mai 2020).

    https://doi.org/10.1016/j.enbuild.2020.109866

  5. Moayedi, Hossein / Mu'azu, Mohammed Abdullahi / Foong, Loke Kok (2020): Novel swarm-based approach for predicting the cooling load of residential buildings based on social behavior of elephant herds. In: Energy and Buildings, v. 206 (Januar 2020).

    https://doi.org/10.1016/j.enbuild.2019.109579

  6. Zhang, Xiliang / Nguyen, Hoang / Bui, Xuan-Nam / Anh Le, Hong / Nguyen-Thoi, Trung / Moayedi, Hossein / Mahesh, Vinyas (2020): Evaluating and Predicting the Stability of Roadways in Tunnelling and Underground Space Using Artificial Neural Network-Based Particle Swarm Optimization. In: Tunnelling and Underground Space Technology, v. 103 (September 2020).

    https://doi.org/10.1016/j.tust.2020.103517

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