Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices by Dong-Rui Chen, Chuang Liu, Yi-Cheng Zhang, Zi-Ke Zhang

“…In addition, we propose an extremes indicator through the network, which is constructed from the price time series using a weighted visual graph algorithm. Experimental results on 12 stock indices show that the proposed indicators can predict financial extremes very well.…”
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Research on incremental deployment mechanism of network modality for polymorphic network environment by Jiong LI, Yuxiang HU, Pengshuai CUI, Le TIAN, Yongji DONG

“…Polymorphic networks support diverse network requirements and can coexist, evolve, and change on a unified physical or logical infrastructure in the form of network modality.They can maximize the innovation vitality of network technology driven by new applications.The evolution and development of modality require the incremental deployment of modality to meet the needs of convenience and privacy protection in the multi-user deployment process.However, the deployment of current network functions still uses the one-by-one deployment method, resulting in high complexity of the deployment of new modality, and mutual exposure of processing logic between different users.To address these issues, an incremental deployment mechanism for polymorphic network environments was proposed.Firstly, an incremental deployment mechanism for network modality was designed.Then, the incremental deployment of modality was abstracted as a graph merging problem based on this mechanism, and an adjacency list-based merge parsing graph algorithm was designed.The simulation results indicate that the proposed mechanism can achieve fast and correct merging of network modality, support incremental modality deployment, and greatly reduce the application deployment and service provision threshold of new network systems.…”
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Research on incremental deployment mechanism of network modality for polymorphic network environment by Jiong LI, Yuxiang HU, Pengshuai CUI, Le TIAN, Yongji DONG

“…Polymorphic networks support diverse network requirements and can coexist, evolve, and change on a unified physical or logical infrastructure in the form of network modality.They can maximize the innovation vitality of network technology driven by new applications.The evolution and development of modality require the incremental deployment of modality to meet the needs of convenience and privacy protection in the multi-user deployment process.However, the deployment of current network functions still uses the one-by-one deployment method, resulting in high complexity of the deployment of new modality, and mutual exposure of processing logic between different users.To address these issues, an incremental deployment mechanism for polymorphic network environments was proposed.Firstly, an incremental deployment mechanism for network modality was designed.Then, the incremental deployment of modality was abstracted as a graph merging problem based on this mechanism, and an adjacency list-based merge parsing graph algorithm was designed.The simulation results indicate that the proposed mechanism can achieve fast and correct merging of network modality, support incremental modality deployment, and greatly reduce the application deployment and service provision threshold of new network systems.…”
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A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis by Can-Zhong Yao, Ji-Nan Lin

“…First, we transform central parity rate time series of US dollar, Euro, Yen, and Sterling against CNY into exchange rate networks with visibility graph algorithm and find consistent topological characteristics in four exchange rate networks, with their average path lengths 5 and average clustering coefficients 0.7. …”
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Algorithm for link prediction in self-regulating network with adaptive topology based on graph theory and machine learning by Evgeny Y. Pavlenko

“…On the basis of the developed model of network functioning with adaptive topology, a graph algorithm for link prediction is proposed, which is extended to the case of peer-to-peer networks. …”
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A robust encrypted traffic identification scheme based on graph neural network by LI Mengxiang, PENG Chuang, WANG Hao, HUANG Chaoming, TAN Xiaobin

“…Compared with the latest ProGraph algorithm, the accuracy is improved by 7.3%, and the experimental results verify the effectiveness of the proposed method.…”
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Assessing the interactions between time series signals using weighted horizontal visibility graphs by Arya Teymourlouei, James Reggia, Rodolphe Gentili

“…The visibility graph algorithm is used to map recorded time series signals to complex networks. …”
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Cyber threat intelligence for smart grids using knowledge graphs, digital twins, and hybrid machine learning in SCADA networks by Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-hani, Hussam Al Hamadi

“…To further enhance the analysis, a directed-graph (DiGraph) algorithm is applied to create a knowledge-graph-based digital twin, allowing for a deeper understanding of how these cyber-attacks impact SCADA operations. …”
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Capturing trial-by-trial variability in behaviour: people with Parkinson’s disease exhibit a greater rate of short-term fluctuations in response times by Hayley J. MacDonald, Ole Bernt Fasmer, Olav T. Jønsi, Lin Sørensen

“…These novel results indicate that a similarity graph algorithm may be a sensitive tool to capture the rapidly varying changes in behaviour that result from dysfunctional dopamine bursting activity in PD.…”
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Partitioning Dichotomous Items Using Mokken Scale Analysis, Exploratory Graph Analysis and Parallel Analysis: A Monte Carlo Simulation by Gomaa Said Mohamed Abdelhamid, María Dolores Hidalgo, Brian F. French, Juana Gómez-Benito

“…In this study we perform simulation-based comparisons of two EGA methods (EGA with graphical least absolute shrinkage and selector operator; EGAtmfg with triangulated maximally filtered graph algorithm), two MSA methods (AISP: automated item selection procedure; GA: genetic algorithm), and two widely used factor analytic techniques (parallel analysis with principal component analysis (PApc) and parallel analysis with principal axis factoring (PApaf)) for partitioning dichotomous items. …”
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DiGraph-Enabled Digital Twin and Label-Encoding Machine Learning for SCADA Network’s Cyber Attack Analysis in Industry 5.0 by Nabeel Al-Qirim, Anoud Bani-Hani, Munir Majdalawieh, Hussam Al Hamadi, Mohammad Kamrul Hasan

“…To process digital twins and determine how the cyberattacks are impacting SCADA components, the directed-graph (DiGraph) algorithm-based knowledge-graph method is utilized. …”
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Analyzing cryptographic algorithm efficiency with in graph-based encryption models by Yashmin Banu, Biplab Kumar Rath, Debasis Gountia

“…This study evaluates RSA and ElGamal encryption on text, image, audio, and data files of varying sizes using graph-based models. The Star graph algorithm is adopted for its simplicity and low computational cost, and its performance is compared against A*, Dijkstra, and Bellman-Ford algorithms. …”
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Research progress of abnormal user detection technology in social network by Qiang QU, Hongtao YU, Ruiyang HUANG

“…In social networks,the problem of anomalous users detection is one of the key problems in network security research.The anomalous users conduct false comments,cyberbullying or cyberattacks by creating multiple vests,which seriously threaten the information security of normal users and the credit system of social networks ,so a large number of researchers conducted in-depth study of the issue.The research results of the issue in recent years were reviewed and an overall structure was summarized.The data collection layer introduces the data acquisition methods and related data sets,and the feature presentation layer expounds attribute features,content features,network features,activity features and auxiliary features.The algorithm selection layer introduces supervised algorithms,unsupervised algorithms and graph algorithms.The result evaluation layer elaborates the method of data annotation method and index.Finally,the future research direction in this field was looked forward.…”
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A Quantum Framework for Combinatorial Optimization Problem over Graphs by Meng Shi, Sai Wu, Ying Li, Gongsheng Yuan, Chang Yao, Gang Chen

“…One key advantage of our framework is that it allows developers to design new graph algorithms for the graph problem represented as linear combinations of edge weights without requiring expertise in quantum programming. …”
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Handheld Ground-Penetrating Radar Antenna Position Estimation Using Factor Graphs by Paweł Słowak, Tomasz Kraszewski, Piotr Kaniewski

“…The system was modeled under realistic conditions, and both the EKF and various factor-graph algorithms were implemented. Comparative evaluation indicates that the factor-graph approach achieves an improvement in localization accuracy from over 30 to almost 50 percent compared to the EKF PND. …”
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Bridge Digital Twin for Practical Bridge Operation and Maintenance by Integrating GIS and BIM by Yan Gao, Guanyu Xiong, Ziyu Hu, Chengzhang Chai, Haijiang Li

“…This study addresses these limitations by developing an integrated DT system that combines WebGIS, WebBIM, and graph algorithms within a three-layer architecture. The system design includes a common data environment (CDE) to address cross-platform compatibility, enabling real-time monitoring, drone-enabled inspection, maintenance planning, traffic diversion, and logistics optimization. …”
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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
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SYNTHESIS OF THE THERMALLY COUPLED DISTILLATION SEQUENCES by E. А. Anokhina, А. V. Timoshenko

“…The only current system approach to the synthesis of ED schemes with coupled thermal and material flows for multicomponent mixtures is the method of graphs (algorithm 4). At present, the first step has been taken to implement it in the form of a computer program. …”
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Toward Greener Matrix Operations by Lossless Compressed Formats by Francesco Tosoni, Philip Bille, Valerio Brunacci, Alessio de de Angelis, Paolo Ferragina, Giovanni Manzini

“…Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and energy efficiency of SpMV using various compressed formats for large sparse matrices, focusing specifically on Boolean matrices and real-valued vectors. …”
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Fairness modeling for topics with different scales in short texts by Chuangying Zhu, Yongyu Liang, Xinyuan Liang, Limiao Zhong, Fei Xie

“…The employment of graph algorithms facilitates the identification of semantically related clusters within the document graph, thereby enhancing the semantic associations between sparse data. …”
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