Postal horse relays and roads in France, from the 17th to the 19th centuries by Nicolas Verdier, Timothée Giraud, Christophe Mimeur, Anne Bretagnolle

Get full text

Learning attribute network algorithm based on high-order similarity by Shaoqing WU, Yihong DONG, Xiong WANG, Yan CAO, Yu XIN

Get full text

Ultra-Short-Term Photovoltaic Power Prediction Based on Predictable Component Reconstruction and Spatiotemporal Heterogeneous Graph Neural Networks by Yingjie Liu, Mao Yang

“…The proposed method is applied to a PV power plant in Gansu, China, and the results show that the prediction method based on the proposed combined spatio-temporal heterogeneous graph neural network model combined with the proposed predictable component extraction achieves an average reduction of 6.50% in the RMSE, an average reduction of 2.50% in the MAE, and an average improvement of 11.93% in the R² over the direct prediction method, respectively.…”
Get full text

Dynamic graph structure and spatio-temporal representations in wind power forecasting by Zang Peng, Dong Wenqi, Wang Jing, Fu Jianglong

Get full text

Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks by Lingyun Li, Jie Zhou, Demin Li, Jinde Cao, Xiaolu Zhang

“…We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. …”
Get full text

Landslide Deformation Uncertainty Quantification Using Conformalized Graph Neural Networks: A Case Study in Sichuan Province, China by Xiaopeng Ren, Wei Liu, Weiqi Yang, Lixuan Mao, Huajin Li

“…This paper presents GNN-CF, a novel framework that integrates Graph Neural Networks (GNN) with Conformal Prediction for reliable interval forecasting of landslide deformation. …”
Get full text

Dynamic climate graph network and adaptive climate action strategy for climate risk assessment and low-carbon policy responses by Fang Zhou, Yan Shi, Pengfei Zhao, Zhengzhao Gu, Ye Li

“…Traditional climate action models often struggle with capturing intricate spatial-temporal dependencies and integrating multi-modal data, resulting in limited scalability and real-world applicability.MethodsTo address these challenges, we propose a novel framework that integrates the Dynamic Climate Graph Network (DCGN) with the Adaptive Climate Action Strategy (ACAS). …”
Get full text

Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…This paper proposes a Multi-scale Frequency domain Feature-based Dynamic graph Attention Network (MFF-DANet) for upper limb MI decoding in hemiplegic patients. …”
Get full text

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data by Kai Wang, Yulong Li, Fei Liu, Xiaoli Luan, Xinglong Wang, Jingwen Zhou

“…Abstract Background A gene regulatory network (GRN) is a graph-level representation that describes the regulatory relationships between transcription factors and target genes in cells. …”
Get full text

Optimization of social security patrol strategy based on graph theory and GGC algorithm by Jian Wang

“…Abstract To cope with complex dynamic patrol environments and maximize the benefits of regional social security patrols, this study abstracts patrol areas as a graph model and constructs a network diagram of the social security patrol area. …”
Get full text

Width‐Based Discharge Partitioning in Distributary Networks: How Right We Are by Jayaram Hariharan, Anastasia Piliouras, Jon Schwenk, Paola Passalacqua

“…We compare data from 15 river deltas to discharge partitioning estimates based on channel network graphs derived from remote sensing imagery. …”
Get full text

A graph-theoretic framework for integrating mobility data into mathematical epidemic models by Razvan G. Romanescu

Get full text

GRE²-MDCL: Graph Representation Embedding Enhanced via Multidimensional Contrastive Learning by Quanjun Li, Weixuan Li, Xiya Zheng, Junhua Zhou, Wenming Zhong, Xuhang Chen, Chao Long

“…However, most graph neural network models require extensive labelled data, limiting their practical applicability. …”
Get full text

Analysis of Aftershocks from California and Synthetic Series by Using Visibility Graph Algorithm by Alejandro Muñoz-Diosdado, Ana María Aguilar-Molina, Eric Eduardo Solis-Montufar, José Alberto Zamora-Justo

“…For this purpose, seismic series preceding and following each earthquake were constructed using a windowing method with different overlaps and the slope of the connectivity (<i>k</i>) versus magnitude (<i>M</i>) graph (<i>k-M</i> slope) and the average degree were computed from the mapped complex networks. …”
Get full text

Differential dynamic functional network connectivity in different motor subtypes of Parkinson's disease by Yu Pan, Hang Qu, Yi Zhao, Zhaoxia Qin, Jiangbing Liu, Wei Wang

“…The graph theory analysis revealed a significantly reduced global network efficiency in patients with PD compared to HCs. …”
Get full text

Complex Network Algorithm for Glossary Formation Context-Related Predictive Terms by Oleg Popov, Adrian Grosu, Sergey Kramarov

“…To form the glossary of prognostic terms, a comprehensive algorithmic approach was applied, integrating a range of conditions that combine the capabilities of network (graph-based) and semantic approaches. This approach includes automatic graph generation, considering ranking in the evaluation of search results, and context-semantic filtering. …”
Get full text

Decoding stress specific transcriptional regulation by causality aware Graph-Transformer deep learning by Umesh Bhati, Akanksha Sharma, Sagar Gupta, Anchit Kumar, Upendra Kumar Pradhan, Ravi Shankar

“…These networks, validated against extensive experimental data, became input to a Graph Transformer deep learning system. …”
Get full text

Estimating intercity human mobility flow from city attributes and intercity relations in physical space and cyberspace via graph attention network by Qingli Shi, Li Zhuo, Qiuping Li, Haiyan Tao

“…Studies have confirmed that city attributes and intercity relations are vital for estimating intercity mobility flow. Moreover, latest graph neural network (GNN) models show great potential for improving flow estimation accuracy. …”
Get full text

MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks by Jianwei Li, Xukun Zhang, Bing Li, Ziyu Li, Zhenzhen Chen

“…Results In this study, we proposed a deep learning method called Multi-source Data Fusion and Graph Neural Networks for Small Molecule-MiRNA Association (MDFGNN-SMMA) to predict potential SM-miRNA associations. …”
Get full text

A novel graph modeling method for GNN-based hypersonic aircraft flow field reconstruction by Qiao Li, Xingchen Li, Xiaoqian Chen, Wen Yao

Get full text