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  1. 161
  2. 162

    Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

    Published 2025-01-01
    “…To further improve feature selection, we utilize the Chaotic Whale Optimization (ChWO) Algorithm, which optimally selects the most relevant attributes from the extracted features. …”
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    Article
  3. 163

    A Study on the Design of a New Three-Dimensional Seismic Isolation Bearing Based on an Improved Genetic Algorithm for Bridge Engineering by Ying Sheng, Zhenchao Yang, Yu Meng, Bin Jia

    Published 2024-10-01
    “…However, passive seismic isolation devices, due to their non-adjustable performance parameters, struggle to achieve effective seismic isolation across a wide frequency range of 0 Hz to 20 Hz in response to random and varying seismic loads. (2) Methods: The sensitivity of the design parameters of the seismic isolation bearing was analyzed using the optimization center gradient method, and an improved genetic algorithm was employed to quickly optimize and obtain the optimal design parameters. (3) Results: The effectiveness of the three-dimensional seismic isolation bearing was validated through experiments. (4) Conclusions: The multi-factor sensitivity analysis approach used in this study for designing novel isolation bearings is applicable not only to seismic design in bridges but also serves as a reference for parameter design in isolation bearings requiring medium to high precision in seismic performance.…”
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  4. 164

    Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization by Perne Mallikarjun, Sundar Rajan Giri Thulasiraman, Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri

    Published 2025-03-01
    “…The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm to optimize energy management and minimize operational costs under varying scenarios. …”
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    Article
  5. 165
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    Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

    Published 2025-12-01
    “…The goals of this study were to (i) identify optimal spectral indices and texture features from RGB and multispectral (MS) images and (ii) improve the accuracy of PNC prediction by combining optimal features with ML. …”
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  7. 167

    Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

    Published 2025-04-01
    “…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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  8. 168

    An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout by Qiangyu Zheng, Peijiang Ding, Zhixin Qin, Zhenguo Yan

    Published 2025-05-01
    “…Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). …”
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  9. 169

    Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

    Published 2025-08-01
    “…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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  10. 170

    Comprehensive recognition algorithm of RS code based on fast code root trial by Xiaolin ZHANG, Xiuqiao LI, Rongchen SUN

    Published 2022-11-01
    “…In order to solve the problem of high computation and high missed alarm probability of RS (Reed-Solomon) codes for recognition, comprehensive recognition algorithm of RS codes based on fast code root trial was proposed.Firstly, the check relationship was solved in binary equivalently and fast code root trial was used to check parameters in sequence.Secondly, according to distribution characteristics of the combined code roots, m-level primitive polynomial field and error correction ability was associatively determined.Finally, the short codes and long codes were given different confidence weights and the determined parameters were comprehensively analyzed.The optimal parameter was selected and the generate polynomial was calculated.The proposed algorithm did not need prior information such as signal-to-noise ratio (SNR), and had good adaptability.The simulation results show that the proposed algorithm can effectively reduce the missed alarm probability under the condition of low complexity.Compared with the conventional hard decision algorithm, the performance of the proposed algorithm is improved, and the parameter recognition of RS codes can be completed quickly.…”
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  11. 171
  12. 172

    Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

    Published 2025-02-01
    “…We also improved several resampling strategies, such as undersampling and oversampling. …”
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    Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

    Published 2025-04-01
    “…To address this issue, this paper proposes a novel prediction model based on the Improved Sparrow Search Algorithm-optimized XGBoost (ISSA-XGBoost). …”
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  17. 177

    A novel swarm intelligence-based approach for solving optimal power flow problems in modern power systems by Haewon Byeon, Wajdi Alghamdi, Munni Evin, M. Sucharitha, D. David Neels Ponkumar, A. Prakash, J. Sunil

    Published 2025-06-01
    “…In order to solve the optimum power flow difficulties related to the C-UPFC, this research suggested an Improved Pelican optimization algorithm (IPOA). Install the superior flexible AC transmission system (FACTS) in accordance with the transmission line (TL) in a series configuration to provide independent voltage control that combines power flow regulation. …”
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  18. 178

    Optimal Performance of PI Controller for AC Microgrid Based on Metaheuristic Optimization Algorithms by Ruqaya Majeed Kareem, Mohammed Kh. Al-Nussairi, Ramazan Bayindir

    Published 2025-01-01
    “…As a result, the parameter values must be carefully selected utilizing the optimization techniques. This work aims to improve the droop controller based on optimized PI controller parameters to control the frequency and voltage of microgrids under various conditions by using three metaheuristic optimization algorithms, Slime Mould Algorithm (SMA), Sine Cosine Algorithm (SCA), and Sparrow Search Algorithm (SSA), and compare with the conventional method. …”
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  19. 179

    A Particle Swarm Optimization-Guided Ivy Algorithm for Global Optimization Problems by Kaifan Zhang, Fujiang Yuan, Yang Jiang, Zebing Mao, Zihao Zuo, Yanhong Peng

    Published 2025-05-01
    “…In recent years, metaheuristic algorithms have garnered significant attention for their efficiency in solving complex optimization problems. …”
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  20. 180

    Identifying, Evaluating and Ranking Effective Factors in Improving the Quality of War Tourism in Iran (Rahyan Noor Travels) by Mohammad Ghasemi, Mohammad Mehdi Mohtadi

    Published 2023-02-01
    “…Due to the uncertainty in determining the importance of the factors based on every criterion, ranking is based on the Fuzzy TOPSIS algorithm. Findings: According to the results, optimizing camp time has been selected as the first and most crucial factor, with a relative proximity index of 0.53467. …”
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