Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Finally, the σWIoU loss function replaces the traditional IoU to accelerate convergence and optimize overall performance. Experiments show that compared to the original YOLOX, the proposed algorithm reduces parameters by 53.41% to 4.164 M and computational load to 12.975G, with mAP increased by 1.3%, detection accuracy reaching 98.81%, and recall achieving 100%. …”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Evolutionary Algorithms and Quantum Computing: Recent Advances, Opportunities, and Challenges by Junaid Ur Rehman, Muhammad Shohibul Ulum, Abdurrahman Wachid Shaffar, Amirul Adlil Hakim, Mujirin, Zaid Abdullah, Hayder Al-Hraishawi, Symeon Chatzinotas, Hyundong Shin

“…Nature-inspired metaheuristics have emerged as promising candidates for fulfilling this optimization role. In this paper, we discuss both of these potential directions at the intersection of evolutionary computing and quantum computing while surveying some of the most promising advancements in these directions. …”
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Constrained Bayesian Optimization: A Review by Sasan Amini, Inneke Vannieuwenhuyse, Alejandro Morales-Hernandez

“…Though it has been widely used to solve various optimization tasks, most of the literature has focused on unconstrained settings, while many real-world problems are characterized by constraints. …”
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GOAL ORIENTED SMART PORTFOLIO OPTIMIZATION by Ayush Deshpande, Rohan Gore, Sankirti Shiravale, Shubham Chougule, Samarth Bahirgonde

“…Portfolio optimization is a critical aspect of investment strategy, which aims to maximize returns while minimizing risk. …”
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A Robust Multi-Objective Evolutionary Framework for Artificial Island Construction Scheduling Under Dynamic Constraints by Tianju Zheng, Liping Sun, Mingwei Li, Guangyao Yuan, Shuqi Li

“…To effectively address the complexities of this model, we develop and employ the Multi-Objective Adaptive Cooperative Evolutionary Marine Genetic Algorithm (MACEMGA). MACEMGA combines cooperative coevolution, adaptive dynamic weighting, dynamic penalty functions, and advanced genetic operators to navigate the solution space efficiently and identify Pareto optimal schedules. …”
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A Comprehensive System to Support Decision Making in Highly Complex Project Portfolio Situations by Efrain Solares, Eduardo Fernandez, Carlos A. Coello Coello, Xochitl Segura Lozano, Reimundo Moreno-Cepeda, Raymundo Diaz

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Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller by Serdar Ekinci, Davut Izci, Ozay Can, Mohit Bajaj, Vojtech Blazek

“…The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. …”
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Short term traffic flow prediction and timing optimization at signalized intersections based on SG-LSTM and particle swarm optimization by Lei Yang, Ruijun Guo

“…The optimized signal timing scheme is derived through the implementation of the particle swarm optimization algorithm in Matlab. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…Abstract This study aims to enhance computational performance while minimizing environmental impact in AI (Artificial Intelligence) and ML (Machine Learning) applications, especially in cybersecurity, by developing energy-efficient models using a multi-objective optimization approach. …”
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Sensitivity Analysis Based on E-TOPSIS Combined with MORIME-Based Multi-Objective Optimization for Sprayer Frame Design Optimization by Shaohao Zhou, Qi Chen, Lihua Zhang

“…Finally, the multi-objective lightweight design of the selected components was performed based on the MORIME algorithm. After optimization, the stress increased by 12.01% and 1.52% under two operating conditions, while deformation increased by 0.647 mm and 0.607 mm, and the frame mass was reduced by 22.754 kg, a decrease of 12.8%. …”
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Dual-target WOA spectrum sharing algorithm based on Stackelberg game by Li ZHANG, Tian LIAO, Yejun HE

“…In order to solve the complex spectrum allocation problem,a dual-target whale optimization algorithm (WOA) with strong parallel computing capabilities was introduced,and a Stackelberg game model was proposed that could effectively reflect the actual spectrum requirements,and a dual-target WOA optimized distributed antenna system (DAS) spectrum sharing scheduling algorithm was designed.Simulation results show that performance comparison is performed from multiple indicators such as optimal pricing and user benefits.The proposed algorithm has a good spectrum sharing allocation effect,can achieve fair and effective spectrum allocation,and provides an important reference for the future communication network spectrum sharing mode.…”
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DATA DRIVEN RULE-BASED PEAK SHAVING ALGORITHM FOR SCHEDULING REFRIGERATORS by Daniel KWEGYIR, Francis Effah BOAFO, Daniel OPOKU, Emmanuel Asuming FRIMPONG

“…This approach aims to minimize energy consumption while maintaining thermal comfort. The algorithm’s performance was evaluated using real-world data from the Spanish Transmission Service Operators (TSO). …”
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A systematic review of deep learning applications in database query execution by Bogdan Milicevic, Zoran Babovic

“…We categorize these approaches into three groups based on how such models are applied: improving performance of index structures and consequently data manipulation algorithms, query optimization tasks, and externally controlling query optimizers through parameter tuning. …”
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Generation of Sparse Antennas and Scatterers Based on Optimal Current Grid Approximation by Tuan Phuong Dang, Manh Tuan Nguyen, Adnan F. Alhaj Hasan, Talgat R. Gazizov

“…To solve this task, we present a novel algorithm based on the optimal current grid approximation for generating sparse scattering structures and evaluating their effectiveness. …”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…The proposed approach integrates the nonlinear representation power of the Volterra filter with a momentum optimization mechanism to enhance convergence speed while maintaining robust steady-state accuracy. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Study on Trajectory Planning for Polishing Free-Form Surfaces of XY-3-RPS Hybrid Robot by Xiaozong Song, Junfeng An, Xingwu Ma

“…Additionally, a hybrid optimization framework combining a genetic algorithm (GA) and local search (LS) is proposed to address the challenges of balancing global optimization with local fine-tuning in traditional trajectory planning methods. …”
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Two-Stage Uncertain UAV Combat Mission Assignment Problem Based on Uncertainty Theory by Haitao Zhong, Rennong Yang, Aoyu Zheng, Mingfa Zheng, Yu Mei

“…The proposed modified PSO exhibits superior performance compared with the ant colony optimization algorithm, enabling the acquisition of an optimal allocation scheme with greater benefits. …”
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