Enhancing Frequency Event Detection in Power Systems Using Two Optimization Methods with Variable Weighted Metrics by Hussain A. Alghamdi, Midrar A. Adham, Umar Farooq, Robert B. Bass

“…The algorithm parameters were optimized using two well-established optimization techniques: Grey Wolf Optimization and Particle Swarm Optimization. …”
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New PSO-GWO-based model for enhancing power quality in electrical networks interconnected with photovoltaic sources by Mehdi Sanaei, Hamidreza Akbari, Zohreh Beheshtipour, Somayeh Mousavi

“…This research endeavors to elucidate how achieving a more refined power pattern in electric networks is attainable by considering the power quality of PV sources. A hybrid Particle Swarm Optimization-Gray Wolf Optimization (PSO-GWO) algorithm is proposed to obtain optimal solutions. …”
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Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO by Songling Pang, Kaidi Fan, Meiyi Huo

“…Compared with traditional methods, the diversity and convergence of particle swarm learning are enhanced, and the optimization performance is improved. …”
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Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

“…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
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Image encryption scheme based on compressed sensing and fractional quantum logistic-tent map by Birong Xu, Ximei Ye, Xiaoyuan Wang, Zhipeng Zhang

“…Moreover, the map is also used for confusion and diffusion. In this encryption algorithm, the plaintext image is first sparsely represented with discrete wavelet transform (DWT). …”
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Research on the Range of Stiffness Variation in a 2D Biomimetic Spinal Structure Based on Tensegrity Structures by Xiaobo Zhang, Zhongcai Pei, Zhiyong Tang

“…Ultimately, the PSO (Particle Swarm Optimization) algorithm is employed to identify the optimal combination of structural parameters for maximizing the stiffness ratio, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>K</mi></mrow><mrow><mi>θ</mi><mo>_</mo><mi>t</mi><mi>i</mi><mi>m</mi><mi>e</mi></mrow></msub></mrow></semantics></math></inline-formula>, of SBTDTS under different constraint conditions. …”
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Research on Ginger Price Prediction Model Based on Deep Learning by Fengyu Li, Xianyong Meng, Ke Zhu, Jun Yan, Lining Liu, Pingzeng Liu

“…By combining seasonal decomposition STL, long and short-term memory network LSTM, attention mechanism ATT and Kolmogorov-Arnold network, a combined STL-LSTM-ATT-KAN prediction model is developed, and the model parameters are finely tuned by using multi-population adaptive particle swarm optimisation algorithm (AMP-PSO). Based on an in-depth analysis of actual data on ginger prices over the past decade, the STL-LSTM-ATT-KAN model demonstrated excellent performance in terms of prediction accuracy: its mean absolute error (MAE) was 0.111, mean squared error (MSE) was 0.021, root mean squared error (RMSE) was 0.146, and the coefficient of determination (R²) was 0.998. …”
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A new APSO-SPC method for parameter identification problem with uncertainty caused by random measurement errors by Peng Zhong, Xuanlong Wu, Li Zhu, Aohao Yang

“…A novel approach, which integrates an advanced particle swarm optimization algorithm (APSO) and the stochastic perturbation collocation method (SPC), is proposed to address this issue, called APSO-SPC for short. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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A Two-Stage Optimization Framework for UAV Fleet Sizing and Task Allocation in Emergency Logistics Using the GWO and CBBA by Yongchao Zhang, Wei Xu, Helin Ye, Zhuoyong Shi

“…We validated our GWO-CBBA framework through extensive simulations against three benchmarks: a standard CBBA with a fixed fleet, a centralized Particle Swarm Optimization (PSO) approach, and a Greedy Heuristic algorithm. …”
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A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF by Zenzen, Roumaissa, Ayadi, Ayoub, Benaissa, Brahim, Belaidi, Idir, Sukic, Enes, Khatir, Tawfiq

“…Comparative evaluations with conventional optimisation algorithms, namely Cuckoo, Bat, and Particle Swarm Optimisation, reveal similar Mean Percentage Error values but with increased result variability, whereas Deep Artificial Neural Network models with varied hidden layer sizes.…”
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Time frequency analysis of elastic wave PSO OMP for defects in flat steel of down conductors by Jing Zhang, Wei Liu, Minghui Bao, Peng Yang, Xuhua Liu, Zhihong Fu

“…To solve this problem, this paper uses the Particle Swarm Optimization Orthogonal Matching Pursuit (PSO-OMP) algorithm to reconstruct the signal, significantly reducing noise. …”
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Research on Site Selection and Capacity Determination of Electric Vehicle Public Charging Stations by Integrating K-Means++ and Improved RODDPSO by B. Huang, Z. Wang, J. Chen, B. Zhou, Y. Zhu, Y. Liu

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FDN: A Real-Time Ensemble Fire Detection Network by Dong Hwan Shin, Jang Mook Kang, Taesu Cheong

“…The proposed model effectively distinguishes between fog and clouds, similar to smoke, and light and sunlight, akin to a real fire using the Partial-Loss-Balanced Task Weighting (P-LBTW) algorithm we develop to reduce negative transfer by partially learning task-specific weights. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This approach fully utilizes all feature map information while minimizing the computational and memory requirements. (2) the neck network structure is optimized using the Vovnet Gsconv Cross Stage Partial module. This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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Neural-Driven heuristic for strip packing trained with Black-Box optimization by Mariusz Kaleta, Tomasz Śliwiński

“…Unlike conventional heuristics, our approach dynamically adapts placement decisions based on a broad set of features describing the current partial solution and remaining items. Through extensive computational experiments, we compare our method against well-known strip packing heuristics, including MaxRects and Skyline-based algorithms. …”
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Proactive Frequency Stability Scheme Based on Bayesian Filters and Spectral Clustering by Gian Paramo, Mario D. Baquedano-Aguilar, Arturo Bretas, Sean Meyn

“…When a disturbance is detected, the state of frequency is predicted a few seconds into the future via a particle filter algorithm. Corrective actions are modeled through a mixed integer linear programming algorithm within system areas established through spectral clustering. …”
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Intelligent controller design of an autonomous system using a social spider optimizer for path navigation and obstacle avoidance by Naimul Hasan, Huma Khan, Shahida Khatoon, Mohammad Sajid

“…The Social Spider Optimizer algorithm optimizes the parameters of the fuzzy controller, while the FLC is responsible for obstacle avoidance. …”
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Multi-objective optimization and parameter sensitivity study on microreactor nuclear power systems by Ersheng You, Yiyi Li, Jianjun Xu, Dianchuan Xing, Haochun Zhang

“…Aiming at the MRNPS based on Brayton cycles, the particle swarm optimization (PSO) method was used to carry out the optimization calculation and analysis of three target parameters: system thermal efficiency, power-to-weight ratio and radiator heat removal area. …”
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A New LQR Optimal Control for a Single-Link Flexible Joint Robot Manipulator Based on Grey Wolf Optimizer by Navid Razmjooy, Mehdi Ramezani, Ali Namadchian

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