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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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Fariha Imam, Petr Musilek and Marek Z. Reformat
Due to aging infrastructure, technical issues, increased demand, and environmental developments, the reliability of power systems is of paramount importance. Utility companies aim to provide uninterrupted and efficient power supply to their customers. To...
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Li Li and Kyung Soo Jun
River flood routing computes changes in the shape of a flood wave over time as it travels downstream along a river. Conventional flood routing models, especially hydrodynamic models, require a high quality and quantity of input data, such as measured hyd...
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Tianyu Xi, Ming Wang, Enjia Cao, Jin Li, Yong Wang and Salanke Umar Sa?ad
The thermal comfort evaluation of the urban environment arouses widespread concern among scholars, and research in this field is mostly based on thermal comfort evaluation indexes such as PMV, PET, SET, UTCI, etc. These thermal comfort index evaluation m...
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Muge Pinar Komu, Hakan Ahmet Nefeslioglu and Candan Gokceoglu
Uncertainties related to runout distances in shallow landslide analyses may not only affect lives but may also result in economic losses. Owing to the increase in shallow landslides, which are especially triggered by heavy rainfall, runout distances have...
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Subin Kim, Heejin Hwang, Keunyeong Oh and Jiuk Shin
The seismically deficient column details in existing reinforced concrete buildings affect the overall behavior of the building depending on the failure type of the column. The purpose of this study is to develop and validate a machine-learning-based pred...
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Changchang Li, Botao Xu, Zhiwei Chen, Xiaoou Huang, Jing (Selena) He and Xia Xie
University students, as a special group, face multiple psychological pressures and challenges, making them susceptible to social anxiety disorder. However, there are currently no articles using machine learning algorithms to identify predictors of social...
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Jiangtao Chen, Jiao Zhao, Wei Xiao, Luogeng Lv, Wei Zhao and Xiaojun Wu
Given the randomness inherent in fluid dynamics problems and limitations in human cognition, Computational Fluid Dynamics (CFD) modeling and simulation are afflicted with non-negligible uncertainties, casting doubts on the credibility of CFD. Scientifica...
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