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Shumin Lai, Longjun Huang, Ping Li, Zhenzhen Luo, Jianzhong Wang and Yugen Yi
In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the p...
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Rui-Yu Li, Yu Guo and Bin Zhang
Nonnegative matrix factorization (NMF) is an efficient method for feature learning in the field of machine learning and data mining. To investigate the nonlinear characteristics of datasets, kernel-method-based NMF (KNMF) and its graph-regularized extens...
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Lu Zhang, Hongyu Yang and Xiping Wu
Air traffic management (ATM) relies on the running condition of the air traffic control sector (ATCS), and assessing whether it is overloaded is crucial for efficiency and safety for the entire aviation industry. Previous approaches to evaluating air tra...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Yong Zhu, Tao Zhou, Shengnan Tang and Shouqi Yuan
Hydraulic axial piston pumps are the power source of fluid power systems and have important applications in many fields. They have a compact structure, high efficiency, large transmission power, and excellent flow variable performance. However, the cruci...
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Kara Combs, Hongjing Lu and Trevor J. Bihl
Artificial intelligence and machine learning (AI/ML) research has aimed to achieve human-level performance in tasks that require understanding and decision making. Although major advances have been made, AI systems still struggle to achieve adaptive lear...
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Fengxu Guan, Siqi Lu, Haitao Lai and Xue Du
Underwater optical imaging devices are often affected by the complex underwater environment and the characteristics of the water column, which leads to serious degradation and distortion of the images they capture. Deep learning-based underwater image en...
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Clara Letessier, Jean Cardi, Antony Dussel, Isa Ebtehaj and Hossein Bonakdari
Given that the primary cause of flooding in Ontario, Canada, is attributed to spring floods, it is crucial to incorporate temperature as an input variable in flood prediction models with machine learning algorithms. This inclusion enables a comprehensive...
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Yizhuo Zhang, Hantao Liu, Xingyu Liu and Huiling Yu
Due to the complex structure of high-canopy-density forests, the traditional individual tree segmentation (ITS) algorithms based on ALS point cloud, which set segmentation threshold manually, is difficult to adequately cover a variety of complex situatio...
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Zhenwei Yang, Hang Lv, Xinyi Wang, Hengrui Yan and Zhaofeng Xu
In recent years, inrush water has hampered the regular mining of coal mines, and the proper identification of the source of inrush water is critical to the prevention and management of water hazards in mines. This paper extracts the standard water chemis...
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