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Hosang Han and Jangwon Suh
The accurate prediction of soil contamination in abandoned mining areas is necessary to address their environmental risks. This study employed a combined model of machine learning and geostatistics to predict the spatial distribution of soil contaminatio...
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Yan Chen and Chunchun Hu
Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of time...
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Yan Jin, Yong Ge, Haoyu Fan, Zeshuo Li, Yaojie Liu and Yan Jia
Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urb...
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Sadeq Khaleefah Hanoon, Ahmad Fikri Abdullah, Helmi Z. M. Shafri and Aimrun Wayayok
Land use and land cover changes driven by urban sprawl has accelerated the degradation of ecosystem services in metropolitan settlements. However, most optimisation techniques do not consider the dynamic effect of urban sprawl on the spatial criteria on ...
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Hengde Zhao, Yuxin Zhao and Xiong Deng
Since ocean mobile observation equipment and numerical models have achieved remarkable results, the combination of the two has become an influential topic. A numerical model provides auxiliary information for the arrangement of observation equipment. As ...
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Liang Gong, Fei Huang, Wei Zhang, Yanming Li and Chengliang Liu
Photosynthesis is one of the key issues for vertical cultivation in plant factories, and efficient natural sunlight utilization requires predicting the light falling on each seedbed in a real-time manner. However, public weather services neither provide ...
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Zhengyan Cui, Junjun Zhang, Giseop Noh and Hyun Jun Park
Traffic prediction is a popular research topic in the field of Intelligent Transportation System (ITS), as it can allocate resources more reasonably, relieve traffic congestion, and improve road traffic efficiency. Graph neural networks are widely used i...
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Zhihao Zhang, Yong Han, Tongxin Peng, Zhenxin Li and Ge Chen
Accurate subway passenger flow prediction is crucial to operation management and line scheduling. It can also promote the construction of intelligent transportation systems (ITS). Due to the complex spatial features and time-varying traffic patterns of s...
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Alyaa Amer, Tryphon Lambrou and Xujiong Ye
The advanced development of deep learning methods has recently made significant improvements in medical image segmentation. Encoder?decoder networks, such as U-Net, have addressed some of the challenges in medical image segmentation with an outstanding p...
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Yong Han, Tongxin Peng, Cheng Wang, Zhihao Zhang and Ge Chen
Accurate prediction of citywide short-term metro passenger flow is essential to urban management and transport scheduling. Recently, an increasing number of researchers have applied deep learning models to passenger flow prediction. Nevertheless, the tas...
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