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   Articles with "multi graph" as a keyword



A new multi-graph approach for selecting the sequential excavation method of civil tunnels

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recommendations! Published in 2019 at "Tunnelling and Underground Space Technology"

DOI: 10.1016/j.tust.2019.102999

Abstract: Abstract Growth of urban population, traffic congestion and global warming emissions, have caused the experts to design and construct large span tunnels even in the complex geotechnical conditions where the selection of tunnel excavation method… read more here.

Keywords: method; excavation method; multi graph; sequential excavation ... See more keywords

Simultaneous multi-well production forecasting and operational strategy awareness in heterogeneous reservoirs: a spatiotemporal attention-enhanced multi-graph convolutional network

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-26664-z

Abstract: Accurate production prediction in the ultra-high water cut stage is crucial for oilfield development. However, uncertainties from operational adjustments, reservoir heterogeneity, and inter-well interference pose significant challenges. Traditional reservoir-engineering methods rely on idealized assumptions and… read more here.

Keywords: spatiotemporal attention; attention enhanced; production; multi graph ... See more keywords

Multi-graph attention fusion graph neural network for remaining useful life prediction of rolling bearings

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recommendations! Published in 2024 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ad5de7

Abstract: Graph neural network (GNN) has the proven ability to learn feature representations from graph data, and has been utilized for the tasks of predicting the machinery remaining useful life (RUL). However, existing methods only focus… read more here.

Keywords: graph attention; multi graph; attention fusion; prediction ... See more keywords

Low Rank Matrix Factorization Algorithm Based on Multi-Graph Regularization for Detecting Drug-Disease Association.

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recommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"

DOI: 10.1109/tcbb.2023.3274587

Abstract: Detecting potential associations between drugs and diseases plays an indispensable role in drug development, which has also become a research hotspot in recent years. Compared with traditional methods, some computational approaches have the advantages of… read more here.

Keywords: rank matrix; low rank; regularization; graph regularization ... See more keywords

Bidirectional Probabilistic Multi-Graph Learning and Decomposition for Multi-View Clustering

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recommendations! Published in 2025 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2025.3574924

Abstract: Graph-based multi-view clustering has attracted remarkable attention due to its impressive performance. However, the typical framework consisting of graph learning and indicator generation may fail to align learned graphs with the underlying data structure due… read more here.

Keywords: multi graph; graph learning; view clustering; multi view ... See more keywords

Region Embedding with Adaptive Correlation Discovery for Predicting Urban Socioeconomic Indicators

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recommendations! Published in 2025 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2025.3631025

Abstract: A recent trend in urban computing involves utilizing multi-modal data for urban region embedding, which can be further expanded in a variety of downstream urban sensing tasks. Many previous studies rely on multi-graph embedding techniques… read more here.

Keywords: region embedding; correlation discovery; region; multi graph ... See more keywords

Social-Aware Collaborative Caching in Edge-User Networks: A Joint Multi-Graph Approach

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recommendations! Published in 2024 at "IEEE Transactions on Network Science and Engineering"

DOI: 10.1109/tnse.2024.3404245

Abstract: Collaborative caching between Edge servers (ES) and user equipment (UE) is a key solution for tackling backhaul congestion, high latency, and low cache hit rates in modern communication networks. However, the limited storage capacity of… read more here.

Keywords: caching edge; edge user; multi graph; edge ... See more keywords

Research on semi-supervised multi-graph classification algorithm based on MR-MGSSL for sensor network

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recommendations! Published in 2020 at "EURASIP Journal on Wireless Communications and Networking"

DOI: 10.1186/s13638-020-01745-x

Abstract: With the advent of the era of network information, the amount of data in network information is getting larger and larger, and the classification of data becomes particularly important. Current semi-supervised multi-map classification methods cannot… read more here.

Keywords: supervised multi; classification; multi graph; semi supervised ... See more keywords

A multi-task transient stability assessment method adapted to topology changes using multi-graph sample and aggregate-attention network

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recommendations! Published in 2024 at "Frontiers in Energy Research"

DOI: 10.3389/fenrg.2023.1321998

Abstract: Transient stability assessment (TSA) plays a pivotal role in guiding power grid risk control strategies. However, it faces challenges when dealing with complex multi-graph inputs generated by pre-fault, fault occurrence, and post-fault states. Meanwhile, most… read more here.

Keywords: transient stability; multi graph; multi; topology ... See more keywords

Mental State Classification Using Multi-Graph Features

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recommendations! Published in 2022 at "Frontiers in Human Neuroscience"

DOI: 10.3389/fnhum.2022.930291

Abstract: We consider the problem of extracting features from passive, multi-channel electroencephalogram (EEG) devices for downstream inference tasks related to high-level mental states such as stress and cognitive load. Our proposed feature extraction method uses recently… read more here.

Keywords: mental state; multi graph; using multi; classification using ... See more keywords

Multi-Graph Multi-Label Learning Based on Entropy

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recommendations! Published in 2018 at "Entropy"

DOI: 10.3390/e20040245

Abstract: Recently, Multi-Graph Learning was proposed as the extension of Multi-Instance Learning and has achieved some successes. However, to the best of our knowledge, currently, there is no study working on Multi-Graph Multi-Label Learning, where each… read more here.

Keywords: multi; multi graph; multi label; graph multi ... See more keywords