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  1. 1221

    Ancestral Dynamic Voting Algorithm for Mutual Exclusion in Partitioned Distributed Systems by Faraneh Zarafshan, Abbas Karimi, S. A. R. Al-Haddad, M. Iqbal Saripan, Shamala Subramaniam

    Published 2013-11-01
    “…This algorithm also prolongs the lifetime of service to mutual exclusion for full and partial topologies especially for the situations where there is no majority. …”
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    Article
  2. 1222

    Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking by Wenjian Zheng, An Chang, Qi Wang, Jianing Shang, Mandi Cui

    Published 2023-01-01
    “…The joint probabilistic data association algorithm is used to calculate the probability that each measurement is associated with its possible source targets, and the particle filter is used to update the tracking status of small and weak targets to achieve real-time tracking of small and weak targets. …”
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    Article
  3. 1223

    A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment by Anagh Awal, Farsuram Pandit

    Published 2024-09-01
    “…This paper offers a thorough examination of the application of these meta-heuristic algorithms to network alignment. It explores a wide range of nature-inspired algorithms, including genetic algorithms, particle swarm optimization, ant colony optimization, and simulated annealing. …”
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    Article
  4. 1224

    Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction by Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

    Published 2024-11-01
    “…This paper presents a novel scanning micromirror calibration method based on the prediction of a particle swarm optimization-least squares support vector machine (PSO-LSSVM). …”
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    Article
  5. 1225

    Improved Grey Wolf Algorithm: A Method for UAV Path Planning by Xingyu Zhou, Guoqing Shi, Jiandong Zhang

    Published 2024-11-01
    “…Compared to Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), GWO, and MP–GWO algorithms, the NI–GWO algorithm can achieve the optimal fitness value and has significant advantages in terms of average path length, time, number of collisions, and obstacle avoidance capabilities.…”
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    Article
  6. 1226

    Comparison of algorithms for multi-objective optimization of radio technical device characteristics by A. V. Smirnov

    Published 2022-12-01
    “…One of the compared algorithms comprises the Third Evolution Step of Generalized Differential Evolution (GDE3) population-based algorithm for searching the full approximation of the Pareto set simultaneously, while the other three algorithms minimize the scalar objective function to find only one element of the Pareto set in a single search cycle: these comprise Multistart Pattern Search (MSPS), Multistart Sequential Quadratic Programming (MSSQP) method and Particle Swarm Optimization (PSO) algorithms.Results. …”
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    Article
  7. 1227

    PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM by Fatimah F. Jaber

    Published 2025-02-01
    “…Nuptial dancing and random flight improve the ability of the algorithm to balance its features of exploitation and exploration while assisting in its escape from local optima. …”
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    Article
  8. 1228

    Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges by Dario Fernando Yépez-Ponce, William Montalvo, Ximena Alexandra Guamán-Gavilanes, Mauricio David Echeverría-Cadena

    Published 2025-06-01
    “…Fifty-seven percent of the recent studies focus on UGV optimization, with prominent applications in agriculture, aiming to maximize efficiency and reduce costs. Heuristic algorithms, such as Humpback Whale Optimization, Firefly Search and Particle Swarm Optimization, are commonly employed to solve complex search problems. …”
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    Article
  9. 1229

    Novel distinguisher for SM4 cipher algorithm based on deep learning by Huijiao WANG, Xin ZHANG, Yongzhuang WEI, Lingchen LI

    Published 2023-07-01
    “…A method was proposed to construct a deep learning distinguisher model for large state block ciphers with large-block and long-key in view of the problem of high data complexity, time complexity and storage complexity of large state block cipher distinguishers, and the neural distinguishers were constructed for SM4 algorithm.Drawing inspiration from the idea that ciphertext difference could improve the performance of distinguishers, a new input data format for neural distinguisher was designed by using partial difference information between ciphertext pairs as part of the training data.The residual neural network model was used to construct the neural distinguisher.The training dataset for large blocks was preprocessed.Additionally, an improved strategy for model relearning was proposed to address the high specificity and low sensitivity of the constructed distinguisher.Experimental results show that the proposed deep learning model for SM4 can achieve 9 rounds neural distinguisher.The accuracy of 4~9 rounds distinguishers can reach up to 100%, 76.14%, 65.20%, 59.28%, 55.89% and 53.73% respectively.The complexity and accuracy of the constructed differential neural distinguisher are significantly better than those of traditional differential distinguishers, and it is currently the best neural distinguisher for the block cipher SM4 to our knowledge.It also proves that the deep learning method is effective and feasible in the security analysis of block cipher of large block.…”
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    Article
  10. 1230

    A Hybrid Strategy Two‐Dimensional Concrete Aggregate Filling Algorithm by Xu Tian, Jun Ao, ChunBo Ma, JunJie Shi, HanJun Guo

    Published 2025-01-01
    “…The results show that the algorithm can rapidly generate more than 75% aggregate packing density concrete specimens and significantly outperforms similar algorithms regarding aggregate placement efficiency and model generation time. …”
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    Article
  11. 1231

    Tri-objective parallel machine with job splitting and sequence dependent setup times using differential evolution and particle swarm optimization by Warisa Wisittipanich, Nuttachat Wisittipanit

    Published 2024-12-01
    “…This study applied two metaheuristic algorithms, namely differential evolution (DE) and particle swarm optimization (PSO) to the tri-objective PMSP with job splitting and sequence dependent setup times (PMSP-JSSDST) in order to obtain solutions with simultaneously minimized makespan, tardiness and total energy consumption. …”
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    Article
  12. 1232

    Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

    Published 2025-04-01
    “…This paper proposes a lightweight framework algorithm based on a contextual semantic fusion model, which is built upon the YOLOv7 model. …”
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    Article
  13. 1233

    Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

    Published 2025-05-01
    “…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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    Article
  14. 1234

    Direct methanol fuel cells parameter identification with enhanced algorithmic technique by Manish Kumar Singla, Muhammed Ali S.A, Ramesh Kumar, Hamed Zeinoddini-Meymand, Farhad Shahnia

    Published 2025-04-01
    “…A number of optimization techniques have been adopted: Particle Swarm Optimization (PSO), Dragonfly Algorithm (DA), Harris Hawk Optimizer (HHO), Rhinoceros Search Algorithm (RSA), Artificial Hummingbird Algorithm (AHA), and its enhanced version, Enhanced artificial hummingbird algorithm (EAHA). …”
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    Article
  15. 1235

    Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

    Published 2025-04-01
    “…Performance test results showed that AROA had a significant advantage in comprehensive optimization performance compared to Genetic Algorithm (GA), Simulated Annealing-Improved Particle Swarm Optimization (SA-IPSO), and Monotonic Basin Hopping (MBH). …”
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    Article
  16. 1236
  17. 1237

    Improving lameness detection in cows: A machine learning algorithm application by Elma Dervić, Caspar Matzhold, Christa Egger-Danner, Franz Steininger, Peter Klimek

    Published 2024-12-01
    “…A Random Forest classifier, using input features selected by the Boruta algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots. …”
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    Article
  18. 1238

    Chameleon swarm algorithm with Morlet wavelet mutation for superior optimization performance by Vipan Kusla, Gurbinder Singh Brar, Harpreet Kaur, Ramandeep Sandhu, Chander Prabha, Md. Mehedi Hassan, Shahab Abdulla, Md Rittique Alam, Samah Alshathri, Walid El-Shafai

    Published 2025-04-01
    “…Five performance metrics—average energy consumption, total energy consumption, total residual energy, dead node and cluster head frequency are taken into consideration when evaluating the performances against state-of-the-art algorithms. For nine different simulation scenarios, the proposed algorithm mCSAMWL outperforms the Atom Search Optimization (ASO), Hybrid Particle Swarm Optimization and Grey Wolf Optimization (PSO-GWO), Bald Eagle Search Algorithm (BES), the African Vulture Optimization Algorithm (AVOA), and the Chameleon Swarm Algorithm (CSA) in terms of average energy consumption and total energy consumption by 50.9%, 52.6%, 45%, 42.4%, 50.1% and 51.4%, 53.3%, 45.6%, 42.4%, 50.7%.…”
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    Article
  19. 1239

    AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

    Published 2025-06-01
    “…Results Simulation results demonstrate that the ISSA significantly outperforms the original SSA and other state-of-the-art algorithms, such as particle swarm optimization (PSO), differential evolution (DE), artificial bee colony (ABC), and whale optimization algorithm (WOA). …”
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    Article
  20. 1240

    Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

    Published 2025-06-01
    “…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
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    Article