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Haiqiang Yang and Zihan Li
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The ap...
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Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
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Jiayao Liang and Mengxiao Yin
With the rapid advancement of deep learning, 3D human pose estimation has largely freed itself from reliance on manually annotated methods. The effective utilization of joint features has become significant. Utilizing 2D human joint information to predic...
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Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
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Jiawei Kang, Shangwen Yang, Xiaoxuan Shan, Jie Bao and Zhao Yang
Exploring the delay causality between airports and comparing the delay propagation patterns across different airport networks is critical to better understand delay propagation mechanisms and provide effective delay mitigation strategies. A novel attenti...
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Yangyang Qi and Zesheng Cheng
In recent years, the rapid economic development of China, the increase of the urban population, the continuous growth of private car ownership, the uneven distribution of traffic flow, and the local congestion of the road network have caused traffic cong...
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Youngsun Jang, Kwanghee Won, Hyung-do Choi and Sung Y. Shin
This study compares the performance of graph convolutional neural network (GCN) models with conventional natural language processing (NLP) models for classifying scientific literature related to radio frequency electromagnetic field (RF-EMF). Specificall...
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Li He, Qian Zhang, Jianyong Duan and Hao Wang
Open-domain event extraction is a fundamental task that aims to extract non-predefined types of events from news clusters. Some researchers have noticed that its performance can be enhanced by improving dependency relationships. Recently, graphical convo...
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Qingyong Zhang, Lingfeng Zhou, Yixin Su, Huiwen Xia and Bingrong Xu
Considering the spatial and temporal correlation of traffic flow data is essential to improve the accuracy of traffic flow prediction. This paper proposes a traffic flow prediction model named Dual Spatial Convolution Gated Recurrent Unit (DSC-GRU). In p...
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Xiaofeng Xu, Pengcheng Liu and Mingwu Guo
Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us...
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