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Yugen Yi, Haoming Zhang, Ningyi Zhang, Wei Zhou, Xiaomei Huang, Gengsheng Xie and Caixia Zheng
As the feature dimension of data continues to expand, the task of selecting an optimal subset of features from a pool of limited labeled data and extensive unlabeled data becomes more and more challenging. In recent years, some semi-supervised feature se...
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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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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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Tingting Wang, Zhuolin Li, Xiulin Geng, Baogang Jin and Lingyu Xu
The accurate prediction of sea surface temperature (SST) is the basis for our understanding of local and global climate characteristics. At present, the existing sea temperature prediction methods fail to take full advantage of the potential spatial depe...
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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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Ibrahim Alkore Alshalabi,Samir E Hamada,Khaled Elleithy,Ioana Badara,Saeid Moslehpour
Pág. pp. 4 - 27
A directed graph represents an accurate picture of course descriptions for online courses through computer-based implementation of various educational systems. E-learning and m-learning systems are modeled as a weighted, directed graph where each node re...
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Miao Tian, Xinxin Hu, Jiakai Huang, Kai Ma, Haiyan Li, Shuai Zheng, Liufeng Tao and Qinjun Qiu
The growing proliferation of geographic information presents a substantial challenge to the traditional framework of a geographic information analysis and service. The dynamic integration and representation of geographic knowledge, such as triples, with ...
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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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Garima Agrawal, Yuli Deng, Jongchan Park, Huan Liu and Ying-Chih Chen
Knowledge graphs gained popularity in recent years and have been useful for concept visualization and contextual information retrieval in various applications. However, constructing a knowledge graph by scraping long and complex unstructured texts for a ...
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Hao Li, Maosheng Hu and Youxin Huang
The identification of overpass structures in road networks has great significance for multi-scale modeling of roads, congestion analysis, and vehicle navigation. The traditional vector-based methods identify overpasses by the methodologies coming from co...
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Yi Li, Nan Wang, Jinlong Li and Yu Zhang
Although the existing deblurring methods for defocused images are capable of approximately recovering clear images, they still exhibit certain limitations, such as ringing artifacts and remaining blur. Along these lines, in this work, a novel deep-learni...
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Vitalii Martovytskyi, Oleksandr Ivaniuk
Pág. 43 - 51
Today, the problem of navigation of autonomous mobile systems in a space where disturbances are possible is urgent. The task of finding a route for a mobile robot is a complex and non-trivial task. At the moment, there are many algorithms that allow you ...
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Zilin Zhao, Zhi Cai, Mengmeng Chang and Zhiming Ding
Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large...
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Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge...
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Yi Wang and Changfeng Jing
Benefiting from the rapid development of geospatial big data-related technologies, intelligent transportation systems (ITS) have become a part of people?s daily life. Traffic volume forecasting is one of the indispensable tasks in ITS. The spatiotemporal...
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Mengmeng Chang, Yuanying Chi, Zhiming Ding, Jing Tian and Yuhao Zheng
In the context of the carbon neutrality target, carbon reduction in the daily operation of the transportation system is more important than that in productive activities. There are few travel services that can quantify low-carbon travel, with a lack of e...
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