Wind Power Forecasting Based on Multi-Graph Neural Networks Considering External Disturbances by Xiaoyin Xu, Zhumei Luo, Menglong Feng

“…Though much progress has been achieved in deep learning approaches, existing methods cannot effectively decompose and model intertwined spatio-temporal dependencies. Current methods typically treat wind power as a unified signal without explicitly separating inherent patterns from external influences, so they have limited prediction accuracy. …”
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Signatures of High‐Latitude Waves in Observations of Geomagnetic Acceleration by Rodrigo Chi‐Durán, Margaret S. Avery, Bruce A. Buffett

“…Magnetic Rossby waves produce a high‐latitude response with suitable phase velocities. However, the spatial complexity of the prediction is not compatible with the observations. …”
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A Heuristic Approach to Competitive Facility Location via Multi-View K-Means Clustering with Co-Regularization and Customer Behavior by Thanathorn Phoka, Praeploy Poonprapan, Pornpimon Boriwan

“…This superiority is evidenced by an approximate 5.21% increase in overall profit and a simultaneous reduction in optimization time, thereby demonstrating its effectiveness in capturing complementary spatial and behavioral structures for competitive facility location. …”
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Simulation of Spring Discharge Using Deep Learning, Considering the Spatiotemporal Variability of Precipitation by Chunmei Ma, Haoyu Jiao, Yonghong Hao, Tian‐Chyi Jim Yeh, Junfeng Zhu, Huiqing Hao, Jiahui Lu, Jiankang Dong

“…Abstract Sparse precipitation data in karst catchments challenge hydrologic models to accurately capture the spatial and temporal relationships between precipitation and karst spring discharge, hindering robust predictions. …”
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Identifying and mapping open-boll cotton fields in the southeastern United States with time series PhenoCam, Sentinel-2 and Sentinel-1 images by Fang Liu, Xiangming Xiao, Yuanwei Qin, Luo Liu

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Introducing the SMAP L4 Products and Investigating the Spatio-Temporal Variability of Soil Moisture in Iran by Ebrahim Asadi Oskouei, Leila Godarzy, Jalil Helali

“…Conclusion: Knowledge of the amount of soil moisture is important in hydrological modeling studies, improving numerical weather prediction (NWP) models, intelligent irrigation in agriculture and climate change. …”
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Cluster Path Planning Method in Mountainous Areas Based on Optimal Timeliness by Zhufeng Shao, Dunwei Gong, Chuansheng Liu

“…A dynamic spatial grid map is used to represent the roller’s surface information, and collision prediction is based on obstacle occupancy and temporal trends. …”
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Unraveling the threshold and interaction effects of environmental variables on soil organic carbon mapping in plateau watershed by Chi Zhang, Yiyun Chen, Yujiao Wei, Peiheng Yu, Yongsheng Hong, Yazhen Hu, Jiaxue Wang, Zhou Shi

“…Understanding the spatial distribution and mechanisms driving soil organic carbon (SOC) is crucial for assessing soil carbon stocks and implementing effective carbon sequestration strategies in agricultural landscapes. …”
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Multi-Parameter Water Quality Inversion in Heterogeneous Inland Waters Using UAV-Based Hyperspectral Data and Deep Learning Methods by Hongran Li, Nuo Wang, Zixuan Du, Deyu Huang, Mengjie Shi, Zhaoman Zhong, Dongqing Yuan

“…Overall, TL-Net significantly improves multi-parameter water quality prediction, captures fine-scale spatial variability, and offers a robust and scalable solution for inland aquatic ecosystem monitoring.…”
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Impact of climate change on the different borders of Iraq's rainy territories by Khudair Ammar Taha

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Multi-Site Air Quality Index Forecasting Based on Spatiotemporal Distribution and PatchTST-Enhanced: Evidence From Hebei Province in China by Wenyi Cao, Rufei Zhang, Wenxin Cao

“…However, few existing models can achieve multi-scale feature fusion and long sequence time series modeling in the prediction process. …”
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Economic benefits of a rural distributed flood storage system by Antonio Arenas, Md Asif Rahman, Aaron Strong, Eric Tate

“…The results are highly sensitive to the geospatial accuracy of exposed buildings, and the flood-reduction benefits diminished at larger spatial scales. …”
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MDGCN: Multiple Graph Convolutional Network Based on the Differential Calculation for Passenger Flow Forecasting in Urban Rail Transit by Chenxi Wang, Huizhen Zhang, Shuilin Yao, Wenlong Yu, Ming Ye

“…Passenger flow forecasting plays an important role in urban rail transit (URT) management. However, complex spatial and temporal correlations make this task extremely challenging. …”
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Assessing climate change impacts on flood risk in the Yeongsan River Basin, South Korea by Agbortoko Bate Ashu, Junsuk Kang

“…Abstract Flood risk prediction is critical for adaptation to the forecast frequency of extreme weather events. …”
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Influence of geometry heterogeneity on Liesegang patterns in rocks by Chong Liu, Klaus Regenauer-Lieb, Manman Hu

“…Our results provide insight into the self-organization processes in geochemical systems and offer a predictive framework for understanding rhythmic mineral banding in rocks.…”
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Quantifying Uncertainties in the Quiet‐Time Ionosphere‐Thermosphere Using WAM‐IPE by Weijia Zhan, Alireza Doostan, Eric Sutton, Tzu‐Wei Fang

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The use of Geographic Information Systems as innovative tools for sustainable development strategies and enhancing the efficiency of forest sector entities by Lutsiv Nataliia, Pavlo Chukhna

“…The study characterized the results of modeling various forest management scenarios. The models utilized satellite sensing data and GIS spatial models that took into account the level of biodiversity conservation, carbon accumulation, and economic benefits. …”
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Impact of Fengyun-4A Atmospheric Motion Vector Data Assimilation on PM_2.5 Simulation by Kaiqiang Gu, Jinyan Wang, Shixiang Su, Jiangtao Zhu, Yu Zhang, Feifan Bian, Yi Yang

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Multiscale Wavelet and Graph Network With Spectral Self-Attention for Hyperspectral Image Classification by Anyembe C. Shibwabo, Zou Bin, Tahir Arshad, Jorge Abraham Rios Suarez

“…Third, DH-GCN constructs a deep graph structure to model spatial topology and overcome oversmoothing. …”
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The formation of the Bicoid morphogen gradient requires protein movement from anteriorly localized mRNA. by Shawn C Little, Gašper Tkačik, Thomas B Kneeland, Eric F Wieschaus, Thomas Gregor

“…In numerical simulations of gradient formation, we find that incorporating the actual bicoid mRNA distribution yields a closer prediction of the observed protein dynamics compared to modeling protein production from a point source at the anterior pole. …”
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