Enhanced Wind Energy Forecasting Using an Extended Long Short-Term Memory Model by Zachary Barbre, Gang Li

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SynthSecureNet: An Improved Deep Learning Architecture with Application to Intelligent Violence Detection by Ntandoyenkosi Zungu, Peter Olukanmi, Pitshou Bokoro

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Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU by Jonathan Decker, Vincent Florens Hasse, Julian Kunkel

“…However, as the majority of Kubernetes clusters operate on homogeneous hardware, most scheduling algorithms are also only developed for homogeneous systems. …”
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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

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Inspiring from Galaxies to Green AI in Earth: Benchmarking Energy-Efficient Models for Galaxy Morphology Classification by Vasileios Alevizos, Emmanouil V. Gkouvrikos, Ilias Georgousis, Sotiria Karipidou, George A. Papakostas

“…Our results reveal that a GPU-optimized multilayer perceptron achieves state-of-the-art accuracy of 98% while emitting 20× less CO₂ than ensemble forests, which—despite comparable accuracy—incur substantially higher energy costs. …”
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Machine Learning Reconstruction of Wyrtki Jet Seasonal Variability in the Equatorial Indian Ocean by Dandan Li, Shaojun Zheng, Chenyu Zheng, Lingling Xie, Li Yan

“…The proposed multi-feature integrated modeling framework delivers a high spatiotemporal resolution analytical tool for tropical Indian Ocean circulation dynamics research, while simultaneously establishing critical data infrastructure to decode monsoon current coupling mechanisms, advancing early warning systems for extreme climatic events, and optimizing regional marine resource governance.…”
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Analysis of Reliability and Efficiency of Information Extraction Using AI-Based Chatbot: The More-for-Less Paradox by Eugene Levner, Boris Kriheli

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Bus Network Adjustment Pre-Evaluation Based on Biometric Recognition and Travel Spatio-Temporal Deduction by Qingbo Wei, Nanfeng Zhang, Yuan Gao, Cheng Chen, Li Wang, Jingfeng Yang

“…Third, the factors influencing passengers’ path selection are analyzed, and a predictive model is built to estimate post-adjustment path choices. A genetic algorithm is employed to optimize the model’s weights. …”
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Experimental realization of PSO-based hybrid adaptive sliding mode control for force impedance control systems by Sarucha Yanyong, Somyot Kaitwanidvilai

“…A sliding surface guarantees system stability, while Particle Swarm Optimization (PSO) optimizes impedance parameters, reducing the risk of local minima. …”
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The Referenced Vertex Ordering Problem: Theory, Applications, and Solution Methods by Omer, Jérémy, Mucherino, Antonio

“…Our results highlight that the newly introduced pruning techniques allow the computation of good-quality solutions (in comparison with other solver’s solutions) while reducing the overall computational cost. Our branch-and-bound outperforms other existing solution methods: among 180 instances with 60 vertices, it solves 179 instances to optimality whereas the best existing method is only able to solve 109 of them. …”
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Predictive analytics in customer behavior: Anticipating trends and preferences by Hamed GhorbanTanhaei, Payam Boozary, Sogand Sheykhan, Maryam Rabiee, Farzam Rahmani, Iman Hosseini

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Fractional hitting sets for efficient multiset sketching by Timothé Rouzé, Igor Martayan, Camille Marchet, Antoine Limasset

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A space-time least-squares support vector regression scheme for inverse source problem of the time-fractional wave equation by A. Mohammadi, A. Tari Marzabad

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Anchorage accurately assembles anchor-flanked synthetic long reads by Xiaofei Carl Zang, Xiang Li, Kyle Metcalfe, Tuval Ben-Yehezkel, Ryan Kelley, Mingfu Shao

“…The optimality is defined as maximizing the weight of the smallest node while matching the estimated sequence length. …”
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Cycle-based formulations in Distance Geometry by Liberti, Leo, Iommazzo, Gabriele, Lavor, Carlile, Maculan, Nelson

“…The problem is often modelled as a mathematical programming formulation involving decision variables that determine the position of the vertices in the given Euclidean space. Solution algorithms are generally constructed using local or global nonlinear optimization techniques. …”
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Adaptive Cut Selection in Mixed-Integer Linear Programming by Turner, Mark, Koch, Thorsten, Serrano, Felipe, Winkler, Michael

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Efficient persistence landscape generation by Taylor Henderson, Robert Simon

“…Our algorithm can determine in optimal O ( n * log ( n ) ) if a given birth-death pair appears in the top- k landscapes. …”
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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

“…This study conducts a comparative evaluation of three bio-inspired optimization algorithms for node localization: Particle Swarm Optimization (PSO), Fruit Fly Optimization Algorithm (FOA), and Drop Mongoose Optimization Algorithm (DMOA). …”
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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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A cooperative jamming resource allocation method based on PSO-SSNOA by Wei Liu, You Chen, Xiaohong Zhao, Dejiang Lu, Tianjian Yang

“…This approach innovatively integrates Particle Swarm Optimization (PSO) with the Nutcracker Optimization Algorithm (NOA), while enhancing the nutcracker’s behavioral patterns through seasonal adaptation strategies. …”
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