Self-similar growth and synergistic link prediction in technology-convergence networks: The case of intelligent transportation systems
Self-similar growth and fractality are important properties found in many real-world networks,
which could guide the modeling of network evolution and the anticipation of new links …
which could guide the modeling of network evolution and the anticipation of new links …
Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
N Giamarelos, EN Zois - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Modern power grids are faced with a series of challenges, such as the ever-increasing
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
[HTML][HTML] An integrated image visibility graph and topological data analysis for extracting time series features
A time series can often be characterized using machine learning techniques, which require
feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized …
feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized …
Graph isomorphism networks for wireless link layer anomaly classification
B Bertalanič, C Fortuna - 2023 IEEE Wireless Communications …, 2023 - ieeexplore.ieee.org
Nowadays, modern man-made infrastructures are being upgraded with information and
communication technologies that form large wireless networks. Such large wireless …
communication technologies that form large wireless networks. Such large wireless …
Visibility Graph Based Wireless Anomaly Detection for Digital Twin Edge Networks
Network softwarization, which shifts hardware-centric functions to software implementations,
is essential for enhancing the agility of cellular and non-cellular wireless networks. This …
is essential for enhancing the agility of cellular and non-cellular wireless networks. This …
Image Encoded Time Series Classification of Small Datasets: An Innovative Architecture Using Deep Learning Ensembles
Convolutional neural networks (CNNs) are often favored for their strong learning abilities in
tackling automatic intelligent models. The classification of time series data streams spans …
tackling automatic intelligent models. The classification of time series data streams spans …
CMI-Net: A unified framework for physiological time series classification with incomplete modalities
Q Shen - Authorea Preprints, 2023 - techrxiv.org
CMI-Net: a Unified Framework for Physiological Time Series Classification with Incomplete
Modalities Page 1 P osted on 7 Sep 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.24099339.v1 …
Modalities Page 1 P osted on 7 Sep 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.24099339.v1 …
Graph Neural Networks Based Anomalous RSSI Detection
B Bertalanič, M Vnučec… - 2023 International Balkan …, 2023 - ieeexplore.ieee.org
In today's world, modern infrastructures are being equipped with information and
communication technologies to create large IoT networks. It is essential to monitor these …
communication technologies to create large IoT networks. It is essential to monitor these …
A Privacy-friendly sequential progressive framework for segmented decision making
P Liu, Z Yu, F Huang - … on Artificial Intelligence of Things and …, 2023 - ieeexplore.ieee.org
To achieve progressive and accurate decision-making for long-term time series data while
meeting the needs of privacy-friendly and early, this paper proposes a universal framework …
meeting the needs of privacy-friendly and early, this paper proposes a universal framework …
[PDF][PDF] 时间序列复杂网络分析中的可视图方法研究综述
**海林， 王杰， 周文浩， 蔡煜， 林伟滨 - 电子学报, 2023 - ejournal.org.cn
可视图是将时间序列转换成复杂网络的重要方法之一, 也是连接非线性信号分析和复杂网络之间
的全新视角, 在经济金融, 生物医学, 工业工程等领域均应用广泛. 可视图的拓扑结构继承了原始 …
的全新视角, 在经济金融, 生物医学, 工业工程等领域均应用广泛. 可视图的拓扑结构继承了原始 …