Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method by Teng Jing, Yu Yang, Weimin Ru

“…Specifically, it achieved a rise time of 0.0049 s, a settling time of 0.0079 s, and a steady-state error of 0.0013 mm. The improved PSO algorithm ensures system stability while delivering faster dynamic response and superior control accuracy.…”
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A spectral Fletcher-Reeves conjugate gradient method with integrated strategy for unconstrained optimization and portfolio selection. by Nasiru Salihu, Sulaiman M Ibrahim, P Kaelo, Issam A R Moghrabi, Elissa Nadia Madi

“…In the context of portfolio selection, the proposed method extended to address the problem of stock allocation, ensuring optimized returns while minimizing risks. Empirical evaluations demonstrate the efficiency of the method, demonstrating significant improvements in computational efficiency and optimization outcomes.…”
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A Framework for Generating S-Box Circuits with Boyer–Peralta Algorithm-Based Heuristics, and Its Applications to AES, SNOW3G, and Saturnin by Yongjin Jeon, Seungjun Baek, Giyoon Kim, Jongsung Kim

“…The gate count in the cipher and the circuit depth must be low to minimize these two metrics. Many optimization strategies have been developed for the linear layer, led by the Boyer–Peralta (BP) algorithm. …”
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Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization. by Ihab Hashem, Viviane De Buck, Seppe Seghers, Jan Van Impe

“…Our approach is inspired by how plants efficiently explore physical space in search of light energy, balancing exploration and exploitation while minimizing biomass cost. The algorithm navigates the objective space without revisiting previously explored areas by solving intermediate SOOPs visualized as branches within this space. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…We construct a communication model for this scenario and propose an improved Dual-Actor Network Softmax Twin Delayed Deep Deterministic Policy Gradient algorithm based on deep reinforcement learning. …”
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Optimization of Smooth Trajectories for Two-Wheel Differential Robots Under Kinematic Constraints Using Clothoid Curves by Wei Zeng, Tifan Xiong, Chao Wang

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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…In this study, we introduced XNANet, a self-attention-based CNN network for image classification. Bayesian optimization has been used to initialize the hyperparameters of the proposed model to improve training on the radiographic images. …”
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Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control by Yeon-Jeong Park, Joon-Ho Cho

“…The method is improved through a combination of numerical calculation, Genetic Algorithms, and LSTM networks, showing approximately 15% better performance compared to conventional methods. …”
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Multi-objective optimization of 200 kW air centripetal turbine based on artificial neural networks by Zideng Wang, Yan Zhang, Yuyang Leng, Jiabao Lai, Zhenzhen Wang, Weixiong Chen

“…The results show that the artificial neural network model can fit the CFD numerical simulation results well, with a coefficient of determination larger than 0.97. Then, after optimizing the artificial neural network model with a genetic algorithm, the total -total efficiency of the air centrifugal turbine was improved by 1.479 %, while the axial thrust was reduced by 1.07 %.…”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…A single radar plot and a cumulative ranking summary illustrate and quantify how MaOSSO outperforms more recent swarm-based algorithms like GWO, MOPSO, and MOGWO. The study describes specific future improvement actions while admitting some constraints on extremely large-scale systems. …”
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CriSALAD: Robust Visual Place Recognition Using Cross-Image Information and Optimal Transport Aggregation by Jinyi Xu, Yuhang Ming, Minyang Xu, Yaqi Fan, Yuan Zhang, Wanzeng Kong

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Advancing In Vivo Molecular Bioimaging With Optimal Frequency Offset Selection and Deep Learning Reconstruction for CEST MRI by Adarsha Bhattarai, Chathumi Samaraweera, Mariano Uberti, Aditya N. Bade, Yutong Liu, Dongming Peng

“…Firstly, we use an optimization algorithm to identify a set of optimal sparse frequency offsets for data collection. …”
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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…It was proven  through the experimental results that  the proposed distance measure Weighted Euclidean distance  had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and )  which confirms that (WED) is the best.…”
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Developing a novel approach for passive damped LCL filter and controller parameter design using PSO algorithm in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul by Thi-Thuy-Minh Tran, Binh-Minh Vu, Oh-Soon Shin

“…In this paper, we present a novel design for unmanned aerial vehicle (UAV) communication networks with wireless backhaul, where an active reconfigurable intelligent surface (ARIS) is deployed to improve connections between a UAV and multiple users, while mitigating channel impairments in complex environments. …”
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Two-layer Optimization Scheduling for Off-grid Microgrids Based on Multi-agent Deep Policy Gradient by Huicong FAN, Zhiguo DUAN, Zhiyong CHEN, Shijia ZHU, Hang LIU, Wenxiao LI, Yang YANG

“…The lower-level model optimizes slow-regulating discrete devices based on mixed-integer second-order cone programming, while the upper-level model optimizes fast-regulating continuous devices using a multi-agent deep policy gradient algorithm. …”
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Enhancing Adaptive Spectrum Access: An Intelligent Reflecting Surface Assisted CRN for Future Wireless Communication by Vishwas Srivastava, Binod Prasad

“…Furthermore, IRS optimization using the GWO yields a 7.1% increase in throughput compared to other meta-heuristic-based IRS optimization methods, and a 47.9% improvement over the unoptimized IRS. …”
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Real-Time Optimization of Discrete Element Models for Studying Asphalt Mixture Compaction Characteristics at the Meso-Scale by Xue Wang, Zifang Wang, Xuanye Luo

“…Among these, discrete element modeling (DEM) has been widely adopted due to its effectiveness in addressing particle-scale problems. However, improving simulation accuracy while maintaining computational efficiency remains a challenge. …”
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