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Electrofacies Estimation of Carbonate Reservoir in the Scotian Offshore Basin, Canada Using the Multi-resolution Graph-Based Clustering (MRGC) to Develop the Rock Property Models
Rock properties in geomechanical models depend on electrofacies. Electrofacies classification is a crucial task for generating accurate rock property...
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DCGNN: a single-stage 3D object detection network based on density clustering and graph neural network
Currently, single-stage point-based 3D object detection network remains underexplored. Many approaches worked on point cloud space without...
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Anomaly detection in smart grid using a trace-based graph deep learning model
Electricity plays a significant role in the everyday lives of people. Researchers have long been interested in the classification problem of electric...
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Clustering
This chapter provides a comprehensive overview of traditional clustering algorithms, which have been fundamental in the field of unsupervised...
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Large-Scale 802.11 Wireless Networks Data Analysis Based on Graph Clustering
This paper analyzes a large-scale dataset of real-world Wi-Fi operating networks, collected from more than 9,000 access points (APs) for 1 year. The...
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Knowledge enhanced graph inference network based entity-relation extraction and knowledge graph construction for industrial domain
With the escalating complexity in production scenarios, vast amounts of production information are retained within enterprises in the industrial...
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Biomedical event causal relation extraction based on a knowledge-guided hierarchical graph network
Biomedical Event Causal Relation Extraction (BECRE) is a challenging task in biological information extraction and plays a crucial role to serve for...
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Consistent multi-view subspace clustering with local structure information
Multi-view subspace clustering has attracted extensive attention in recent years because it can fully utilize the inherent characteristics of each...
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A survey on deep clustering: from the prior perspective
Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional...
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Graph convolutional network-based semi-supervised feature classification of volumes
AbstractFeature classification has always been one of the research hotspots in scientific visualization. However, conventional interactive feature...
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Matching maps based on the Area Graph
Topological maps are often used in robotics. This paper presents a novel topological map representation, the Area Graph, and how to extract it from...
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D-GridMST: Clustering Large Distributed Spatial Databases
In this paper, we will propose a novel distributable clustering algorithm, called Distributed-GridMST (D–GridMST for short), which deals with large...
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Autonomous acquisition of arbitrarily complex skills using locality based graph theoretic features: a syntactic approach to hierarchical reinforcement learning
With the growing state/action space, learning a satisfactory policy for regular Reinforcement Learning (RL) algorithms such as flat Q-learning...
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Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems
Clustering is an unsupervised learning technology, and it groups information (observations or datasets) according to similarity measures. Develo**...
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Coalitional graph game for area maximization of multi-hop clustering in vehicular ad hoc networks
Road traffic information can be utilized in many applications of intelligent transport systems. It can be collected from vehicles and sent over a...
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DSMSA-Net: Deep Spatial and Multi-scale Attention Network for Road Extraction in High Spatial Resolution Satellite Images
Road segmentation in high spatial resolution satellite images is an important research topic and has numerous applications in traffic monitoring and...
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Flight risk evaluation based on flight state deep clustering network
Flight risk evaluation based on data-driven approach is an essential topic of aviation safety management. Existing risk analysis methods ignore the...
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Spark-Based Label Diffusion and Label Selection Community Detection Algorithm for Metagenome Sequence Clustering
It is a challenge to assemble an enormous amount of metagenome data in metagenomics. Usually, metagenome cluster sequence before assembly accelerates...
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Extraction method of typical IEQ spatial distributions based on low-rank sparse representation and multi-step clustering
Indoor environment quality (IEQ) is one of the most concerned building performances during the operation stage. The non-uniform spatial distribution...
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Development of hierarchical two-stage constrained spectral clustering algorithm to enhance power system distribution network resiliency under zonal attacks
The power grid is intended to deliver electric power from large, remote power generation units to end-consumers in residential, commercial, and...
