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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Sideris Kiratsoudis and Vassilis Tsiantos
Personnel selection stands as a pivotal component within the domain of human resource management, intrinsically tethered to the quality of the workforce at large. In this research endeavor, we introduce the Entropy Synergy Analysis of Multi-Attribute Dec...
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Yangqing Xu, Yuxiang Zhao, Qiangqiang Jiang, Jie Sun, Chengxin Tian and Wei Jiang
During the construction of deep foundation pits in subways, it is crucial to closely monitor the horizontal displacement of the pit enclosure to ensure stability and safety, and to reduce the risk of structural damage caused by pit deformations. With adv...
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Mahammad Khalid Shaik Vadla, Mahima Agumbe Suresh and Vimal K. Viswanathan
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review data. The pre-tra...
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Xing-Zhou Li, Zhong-Ren Peng, Qingyan Fu, Qian Wang, Jun Pan and Hongdi He
Air pollution is a growing concern in metropolitan areas worldwide, and Shanghai, as one of the world?s busiest ports, faces significant challenges in local air pollution control. Assessing the contribution of a specific port to air pollution is essentia...
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Weilong Guang, Peng Wang, Jinshuai Zhang, Linjuan Yuan, Yue Wang, Guang Feng and Ran Tao
Predicting the flow situation of cavitation owing to its high-dimensional nonlinearity has posed great challenges. To address these challenges, this study presents a novel reduced order modeling (ROM) method to accurately analyze and predict cavitation f...
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Anestis Kousis and Christos Tjortjis
In recent years, the emergence of the smart city concept has garnered attention as a promising innovation aimed at addressing the multifactorial challenges arising from the concurrent trends of urban population growth and the climate crisis. In this stud...
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Cai Wu, Yanwen Wang, Jiong Wang, Menno-Jan Kraak and Mingshu Wang
This study introduces a machine learning-based framework for mapping street patterns in urban morphology, offering an objective, scalable approach that transcends traditional methodologies. Focusing on six diverse cities, the research employed supervised...
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Ce Liang, Jun Zhu, Jinbin Zhang, Qing Zhu, Jingyi Lu, Jianbo Lai and Jianlin Wu
It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geogr...
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