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Amelia Amelia,Tri Diana
Pág. 1 - 19
Abstract: The research aims to analyze the effect of fiscal balance fund on income inequality in West Kalimantan by considering spatial inter-relationships between existing districts/cities. The study showed that the Spatial Durbin Model with fixed ...
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Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)...
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Mengxiao Liu, Yong Ge, Shan Hu and Haiguang Hao
Recognizing the spatial effects of regional poverty is essential for achieving sustainable poverty alleviation. This study investigates these spatial effects and their determinants across three distinct administrative levels within Hubei Province, China....
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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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Matthias Langer, David Durán-Rodas, Elias Pajares
Pág. 87 - 104
While discussions are ongoing about the exact meaning of car dependence, its assessment has been primarily qualitative. The few quantitative approaches adopted so far have tended to analyze either high car use and ownership or a lack of public transport ...
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Brian Skahill, Cole Haden Smith, Brook T. Russell and John F. England
Max-stable process (MSP) models can be fit to data collected over a spatial domain to estimate areal-based exceedances while accounting for spatial dependence in extremes. They have theoretical grounding within the framework of extreme value theory (EVT)...
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Zhenxin Li, Yong Han, Zhenyu Xu, Zhihao Zhang, Zhixian Sun and Ge Chen
Traffic forecasting has always been an important part of intelligent transportation systems. At present, spatiotemporal graph neural networks are widely used to capture spatiotemporal dependencies. However, most spatiotemporal graph neural networks use a...
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Chunwei Hu, Xianfeng Liu, Sheng Wu, Fei Yu, Yongkun Song and Jin Zhang
Accurate crowd flow prediction is essential for traffic guidance and traffic control. However, the high nonlinearity, temporal complexity, and spatial complexity that crowd flow data have makes this problem challenging. This research proposes a dynamic g...
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Venera Timiryanova, Irina Lakman, Vadim Prudnikov and Dina Krasnoselskaya
The price of market products is the result of the interaction of supply and demand. However, within the same country, prices can vary significantly, especially during crisis periods. The purpose of this study is to identify patterns in the changing spati...
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Guoyan Xu, Yuwei Lu, Zixu Jing, Chunyan Wu and Qirui Zhang
The accuracy of dam deformation prediction is a key issue that needs to be addressed due to the many factors that influence dam deformation. In this paper, a dam deformation prediction model based on IEALL (IGWO-EEMD-ARIMA-LSTM-LSTM) is proposed for a si...
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