5 results for “Graph Attention Network”

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Research ArticleOpen accessPhrase in the titleAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,157 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 413 accessesView PDF Cite

Research ArticleOpen accessIn the abstractApplication of Graph Theory Concepts in Computer Networks and its Suitability for the Resource Provisioning Issues in Cloud Computing-A ReviewKanniga Devi Rangaswamy, Murugaboopathi GurusamyCloud computing, a kind of web service provisioning model, provides immense benefits over traditional IT service environments with the help of virtualization technology. As cloud computing is not a fully matured paradigm, it poses many open issues to be addressed. The key research problem in cloud computing is efficient resource provisioning which is due to its complex and distributed architecture. … …Journal of Computer Science, Vol. 14, Issue 2 · 18 Jan 2018 · 8,984 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordFramework of Regression-Based Graph Matrix Analysis Approach in Multi-Relational Social Network ProblemFord Lumban Gaol, Belawati WidjajaCommunity mining is one of the major directions in social network analysis. Social network analysis has attracted much attention in recent years. Most of the existing methods on community mining assume that there is only one kind of relation in the network and moreover, the mining results are independent of the users’ needs or preferences. However, in reality, there exist … …Journal of Mathematics and Statistics, Vol. 4, Issue 1 · 31 Mar 2008 · 6,922 accessesView PDF Cite