CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…The segmentation of tunnel lining cracks is often hindered by the influence of complex environmental factors, which makes relying solely on local feature extraction insufficient for achieving high segmentation accuracy. …”
Get full text

T-RippleGNN: Predicting traffic flow through ripple propagation with attentive graph neural networks. by Anning Ji, Xintao Ma

“…Then, a GRU-based model is used to explore the traffic model through the timeline. Lastly, those two factors are combined and attention scores are assigned to differentiate their influences on the traffic flow prediction. …”
Get full text

The Air Transportation System as a Subsystem of Modern Communication Space: Analysis Based on Transfer Entropy Graphs by Sagit Valeev, Natalya Kondratyeva

Get full text

Origin-destination prediction from road average speed data using GraphResLSTM model by Guangtong Hu, Jun Zhang

“…We use a real-world road network to generate road average speed data and OD data through simulations in Simulation of Urban Mobility (SUMO), thereby avoiding the influence of external factors such as weather. To enhance training efficiency, we employ a method combining the entropy weight method with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for key road segment selection. …”
Get full text

Modeling and experimental validation of a 2D electro-hydraulic servo proportional valve by bond graph by Hao Xu, Feixiang Jin, Tingbo Hou, Wangpiao Lin, Dexun Zhang

“…This paper presents the development of a bond graph model for a 2D electro-hydraulic servo proportional valve (2D-EHSPV), which accounts for nonlinear factors such as magnetic hysteresis, Coulomb friction, and flow force. …”
Get full text

LoadSeer: Exploiting Tensor Graph Convolutional Network for Power Load Forecasting With Spatio-Temporal Characteristics by Jiahao Zhang, Bin Yu, Hanbin Lai, Lin Liu, Jinghui Zhou, Fengliang Lou, Yili Ni, Yan Peng, Ziheng Yu

“…Existing spatio-temporal prediction methods can only handle one factor in each dimension of time and space. In reality, power load is influenced by various factors. …”
Get full text

Impact of Geopolitical and International Trade Dynamics on Corporate Vulnerability and Insolvency Risk: A Graph-Based Approach by Yu Zhang, Elena Sánchez Arnau, Enrique A. Sánchez Pérez

“…The mechanisms that relate geopolitical factors, such as trade sanctions and international conflicts, with the oscillations in the global market are analyzed. …”
Get full text

Relationship Between Career Adaptability and Job Crafting by Mariana de Almeida Klotz Teixeira, Milena Miyuki Hiratuca Ujihara, Rita Pimenta de Devotto, Clarissa Pinto Pizarro de Freitas, Jaqueline de Carvalho Rodrigues

Get full text

Influence of Helicobacter pylori-derived outer membrane vesicles (OMVs) on Snail/β-Catenin cascade and metastasis-related proteins in 4T1 breast cancer cells by Seyedeh Shadi Vaziri, Elahe Tajbakhsh, Faham Khamesipour, Hassan Momtaz

Get full text

On Traffic Prediction With Knowledge-Driven Spatial–Temporal Graph Convolutional Network Aided by Selected Attention Mechanism by Yuwen Qian, Tianyang Qiu, Chuan Ma, Yiyang Ni, Long Yuan, Xiangwei Zhou, Jun Li

“…The urban road network presents a complex web of interconnected roads, where the state of traffic on one road can influence the conditions of others. Moreover, the prediction of traffic conditions necessitates the consideration of diverse temporal factors. …”
Get full text

Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…By analyzing the whole process of wind power generation, the influencing factors of wind power and the interrelation among them are explored, and the GCN model is built. …”
Get full text

Methods for assessing the connectivity of an undirected bipolar labeled graph taking into account the destructive impact of external threats on its vertices by V. A. Voevodin, N. A. Krahotin

“…The main limiting factor is that existing methods are based on probabilistic stationary models that require representative statistics. …”
Get full text

DHGAR: Multi-Variable-Driven Wind Power Prediction Model Based on Dynamic Heterogeneous Graph Attention Recurrent Network by Mingrui Xu, Ruohan Zhu, Chengming Yu, Xiwei Mi

“…Wind power generation is influenced not only by historical data, but also by turbine conditions and external environmental factors, such as weather. …”
Get full text

Multi-Source Data-Driven Local-Global Dynamic Multi-Graph Convolutional Network for Bike-Sharing Demands Prediction by Juan Chen, Rui Huang

“…In this study, we examine various spatiotemporal influencing factors associated with bike-sharing and propose the Local-Global Dynamic Multi-Graph Convolutional Network (LGDMGCN) model, driven by multi-source data, for multi-step prediction of station-level bike-sharing demand. …”
Get full text

Modeling Multivariable Associations and Inter-Eddy Interactions: A Dual-Graph Learning Framework for Mesoscale Eddy Trajectory Forecasting by Yanling Du, Bin Zhang, Jian Wang, Zhenli Qian, Wei Song

“…However, mesoscale eddies are influenced by numerous stochastic and uncertain factors, leading to substantial fluctuations in their attribute variables. …”
Get full text

A Knowledge Graph-Enhanced Hidden Markov Model for Personalized Travel Routing: Integrating Spatial and Semantic Data in Urban Environments by Zhixuan Zeng, Jianxin Qin, Tao Wu

“…The KHMM expands the state space of the traditional Hidden Markov Model using a knowledge graph, enabling the integration of multi-dimensional POI information and higher-order relationships. …”
Get full text

A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…These prevent complex, multifaceted factors influencing crop growth and yield from being captured. …”
Get full text

Gender, kinship, and other social predictors of incrimination in the inquisition register of Bologna (1291-1310): Results from an exponential random graph model. by David Zbíral, Katia Riccardo, Tomáš Hampejs, Zoltán Brys

“…We used social network analysis and, more specifically, an Exponential Random Graph Model (ERGM) to assess the influence of four social predictors: gender, churchperson status, membership of the urban "middle class", and kinship ties between incriminators and the incriminated. …”
Get full text

Exploring a long short-term memory for mountain flood forecasting based on watershed-internal knowledge graph and large language model. by Songsong Wang, Ouguan Xu

“…The water levels associated with mountain floods exhibit rapid fluctuations within small watersheds, necessitating extensive data on various factors influencing such disasters to facilitate real-time forecasting. …”
Get full text

Pre- and Post-harvest Application of Ethylene in Bulb Onion (Allium Cepa l.) Hybrid 'Burguesa' Using Plithogenic n-SuperHyperGraphs by Giovana Paulina Parra Gallardo, Alicia Maribel Gualan Gualan, María Monserrath Morales Padilla

“…conservation for the agricultural industry. This study analyzed factors influencing the preservation of these characteristics throughout the production cycle, with a focus on the impact of ethylene treatments during various storage and conservation stages. …”
Get full text