Multi video stream collaborative adaptive offloading scheme based on equilibrium game theory by Shijun Yuan

“…Secondly, an adaptive task offloading algorithm based on game theory and Nash equilibrium is designed to achieve optimal node selection through offloading algorithm and weight allocation, minimizing the processing cost of the entire multi video stream system and balancing video stream computation latency and energy consumption; Finally, the simulation results show that the proposed scheme satisfies long-term MEC energy constraints while significantly outperforming existing benchmark research schemes in terms of cost performance.…”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Parallel strategies for a multi-criteria GRASP algorithm Estratégias de paralelização para um algoritmo GRASP multicritério by Dalessandro Soares Vianna, José Elias Claudio Arroyo, Pedro Sampaio Vieira, Thiago Ribeiro de Azeredo

“…The computational results show that the proposed parallel algorithms reduce the execution time and the results obtained by the sequential version were improved.…”
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Resource Scheduling with Uncertain Execution Time in Cloud Computing by LI Cheng-yan, CAO Ke-han, FENG Shi-xiang, SUN Wei

“…For the problem of cloud computing resource scheduling, based on the fuzzy programming theory, a fuzzy cloud resource scheduling model under timecost constraint was set up, the uncertain execution time of tasks is represented by the triangular fuzzy number, and the target is to minimize the average value and standard deviation of the evaluation function An improved chaotic ant colony algorithm was proposed to solve the model, the elitist strategy is introduced to optimize the pheromone updating, a chaotic mapping with infinite folding times is used for chaotic search, and the adaptive chaotic disturbance mechanism is designed to enhance the global searching ability The model and algorithm were tested on the Cloudsim platform, the reliability of the model was proved, and the experimental results showed that the proposed algorithm had better performance in convergence speed, solution ability and load balance…”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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EDECO: An Enhanced Educational Competition Optimizer for Numerical Optimization Problems by Wenkai Tang, Shangqing Shi, Zengtong Lu, Mengying Lin, Hao Cheng

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Design and Optimization of a Robust Wide‐Area Damping Controller for Mitigating Inter‐Area Oscillations in Wind‐Integrated Power Systems by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Sun‐Kyoung Kang, Ilhami Colak, El Manaa Barhoumi

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Dynamic neutrosophic cognitive map with improved cuckoo search algorithm (DNCM-ICSA) and ensemble classifier for rheumatoid arthritis (RA) disease by B. Chithra, R. Nedunchezhian

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Scaling of hardware-compatible perturbative training algorithms by B. G. Oripov, A. Dienstfrey, A. N. McCaughan, S. M. Buckley

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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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Non-Convex Split Feasibility Problems: Models, Algorithms and Theory by Gibali, Aviv, Sabach, Shoham, Voldman, Sergey

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Generation Algorithms for Thévenin and Norton Equivalent Circuits by Mihaela Grib, Ioana-Gabriela Sirbu, Lucian Mandache, Marilena Stanculescu, Mihai Iordache, Lavinia Bobaru, Dragos Niculae

“…They use the symbolic computation of two simulation tools developed by our research team. …”
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Value of Low Tube Voltage Combined with Deep Learning Image Reconstruction Algorithm to Reduce Radiation Dose in Combined Thoracoabdominal Enhanced CT by Weiwei QI, Jin CHENG, Chuhan CHEN, Bei AN, Xiaoyi LIU, Ling FU, Yi WANG

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Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization by Jiong Li, Jinlin Zhang, Jikun Ye, Lei Shao, Xiangwei Bu

“…Furthermore, a heuristic initial trajectory generation scheme was devised, and the solution was obtained via a sequential convex programming (SCP) algorithm. Numerical simulation results demonstrated that the proposed method effectively satisfies strict path constraints, successfully generates feasible midcourse guidance trajectories, and exhibits strong computational efficiency and robustness. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
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The open-closed mod-minimizer algorithm by Ragnar Groot Koerkamp, Daniel Liu, Giulio Ermanno Pibiri

“…Abstract Sampling algorithms that deterministically select a subset of $$k$$ k -mers are an important building block in bioinformatics applications. …”
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An intelligent object detection and classification framework for assisting visually challenged persons using deep learning and improved crow search optimization by Alaa O. Khadidos, Ayman Yafoz

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Game algorithm based on link quality: Wireless sensor network routing game algorithm based on link quality by Zhanjun Hao, Jiaojiao Hou, Jianwu Dang, Xiaochao Dang, Nanjiang Qu

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Quantum DeepONet: Neural operators accelerated by quantum computing by Pengpeng Xiao, Muqing Zheng, Anran Jiao, Xiu Yang, Lu Lu

“…Given the progress in quantum algorithms and hardware, here we propose to utilize quantum computing to accelerate DeepONet evaluations, yielding complexity that is linear in input dimensions. …”
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Stability of feature selection algorithm: A review by Utkarsh Mahadeo Khaire, R. Dhanalakshmi

“…This actually questions the interpretability and stability of traditional feature selection algorithms. The high correlation in features frequently produces multiple equally optimal signatures, which makes traditional feature selection method unstable and thus leading to instability which reduces the confidence of selected features. …”
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