Items where Author is "Mohammed, Ahmed Salih"

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Number of items: 7.

Article

Wang, Jiangfeng and Mohammed, Ahmed Salih and Macioszek, Elzbieta and Ali, Mujahid and Ulrikh, Dmitrii Vladimirovich and Fang, Qiancheng (2022) A novel combination of PCA and machine learning techniques to select the most important factors for predicting tunnel construction performance. Buildings, 12 (7). ISSN 2075-5309, DOI https://doi.org/10.3390/buildings12070919.

He, Biao and Lai, Sai Hin and Mohammed, Ahmed Salih and Sabri, Mohanad Muayad Sabri and Ulrikh, Dmitrii Vladimirovich (2022) Estimation of blast-induced peak particle velocity through the improved weighted random forest technique. Applied Sciences-Basel, 12 (10). ISSN 2076-3417, DOI https://doi.org/10.3390/app12105019.

Zeng, Jie and Mohammed, Ahmed Salih and Mirzaei, Fatemeh and Moosavi, Seyed Mohammad Hossein and Armaghani, Danial Jahed and Samui, Pijush (2022) A parametric study of ground vibration induced by quarry blasting: An application of group method of data handling. Environmental Earth Sciences, 81 (4). ISSN 1866-6280, DOI https://doi.org/10.1007/s12665-022-10239-6.

Huat, Chia Yu and Moosavi, Seyed Mohammad Hossein and Mohammed, Ahmed Salih and Armaghani, Danial Jahed and Ulrikh, Dmitrii Vladimirovich and Monjezi, Masoud and Lai, Sai Hin (2021) Factors influencing pile friction bearing capacity: Proposing a novel procedure based on gradient boosted tree technique. Sustainability, 13 (21). ISSN 2071-1050, DOI https://doi.org/10.3390/su132111862.

Li, Yan and Hishamuddin, Fathin Nur Syakirah and Mohammed, Ahmed Salih and Armaghani, Danial Jahed and Ulrikh, Dmitrii Vladimirovich and Dehghanbanadaki, Ali and Azizi, Aydin (2021) The effects of rock index tests on prediction of tensile strength of granitic samples: A neuro-fuzzy intelligent system. Sustainability, 13 (19). ISSN 2071-1050, DOI https://doi.org/10.3390/su131910541.

Zeng, Jie and Roussis, Panayiotis C. and Mohammed, Ahmed Salih and Maraveas, Chrysanthos and Fatemi, Seyed Alireza and Armaghani, Danial Jahed and Asteris, Panagiotis G. (2021) Prediction of peak particle velocity caused by blasting through the combinations of boosted-chaid and svm models with various kernels. Applied Sciences, 11 (8). ISSN 2076-3417, DOI https://doi.org/10.3390/app11083705.

Zeng, Jie and Asteris, Panagiotis G. and Mamou, Anna P. and Mohammed, Ahmed Salih and Golias, Emmanuil A. and Armaghani, Danial Jahed and Faizi, Koohyar and Hasanipanah, Mahdi (2021) The effectiveness of ensemble-neural network techniques to predict peak uplift resistance of buried pipes in reinforced sand. Applied Sciences, 11 (3). p. 908. ISSN 2076-3417, DOI https://doi.org/10.3390/app11030908.

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