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Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so...
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Davide Fronzi, Gagan Narang, Alessandro Galdelli, Alessandro Pepi, Adriano Mancini and Alberto Tazioli
Forecasting of water availability has become of increasing interest in recent decades, especially due to growing human pressure and climate change, affecting groundwater resources towards a perceivable depletion. Numerous research papers developed at var...
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Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
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Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
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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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Zhiqing Guo, Xiaohui Chen, Ming Li, Yucheng Chi and Dongyuan Shi
Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction me...
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Zhihong Chang, Chunsheng Liu and Jianmin Jia
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highwa...
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Qinmeng Yang, Ningming Nie, Yangang Wang, Xiaojing Wu, Weihua Liu, Xiaoli Ren, Zijian Wang, Meng Wan and Rongqiang Cao
Gross primary productivity (GPP) is an important indicator in research on carbon cycling in terrestrial ecosystems. High-accuracy GPP prediction is crucial for ecosystem health and climate change assessments. We developed a site-level GPP prediction meth...
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Jing Tian, Zilin Zhao and Zhiming Ding
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user?s check-in behavior at the current moment by analyzing and mining th...
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Yakob Umer, Victor Jetten, Janneke Ettema and Gert-Jan Steeneveld
This study configures the Weather Research and Forecasting (WRF) model with the updated urban fraction for optimal rainfall simulation over Kampala, Uganda. The urban parameter values associated with urban fractions are adjusted based on literature revie...
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