Servo System Control of Turntable Lipstick-Filling Machine Based on Particle Swarm Optimization by Xiangqiang Zhong, Wenbo Tao, Lingling Zou, Huaian Yang, Shunyu Yao

“…The experimental results demonstrate that the qualified rate of lipstick filling, under the particle swarm optimization PID control implementation, is 97%, indicating that the particle swarm algorithm is quite applicable and has an economic impact by improving the accuracy and stability of the lipstick-filling servo system.…”
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Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation by Spyridon Evangelatos, Eleni Veroni, Mariza Konidi, Sophia Karagiorgou, Georgia Dede, Anargyros Baklezos, Christos Nikolopoulos, Panagiotis Sarigiannidis, Sotirios K. Goudos

“…Static and centralized security models are no longer sufficient to address these challenges, underscoring the need for intelligent, distributed solutions that can optimize policy deployment in real-time. …”
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An Opportunistic Array Beamforming Technique Based on Binary Multiobjective Wind Driven Optimization Method by Zhenkai Zhang, Sana Salous, Hailin Li, Yubo Tian

“…Firstly, the emitted signal model and objective functions of optimization are presented. …”
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Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation by Yue You, Hua Wang, Christophe Paccolat, Volker Gass, Jean-Philippe Thiran, Jiu Ren Li

“…Multi-impulsive Hill guidance law is employed in closed-loop linear covariance analysis model, based on which the quantitative relative position robustness and relative velocity robustness index are defined. …”
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Application of a generative adversarial network algorithm to filling blank strips of fractures in formation microresistivity imaging images by Zhengming KANG, Chensheng WU, Guodong YANG, Disheng WU, Ruifei WANG, Xiangyu YANG, Wei GAN

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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…The method integrates a conventional proportional derivative control algorithm with Bayesian optimization to rapidly determine optimal control parameters without a precise system model and adaptively re-tune these parameters in response to fluctuations in patient respiratory conditions. …”
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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…This necessitates tracking algorithms capable of both target state estimation and prediction. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. Notably, compared to Hourglass, HRNet, and HigherHRNet, YOLORM reduced parameters by 99.3%, 92.9%, and 96.8%, and computational cost by 98.8%, 90.2%, and 95.3%, respectively, while concurrently improving precision and recall. …”
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Mechanism–Data Collaboration for Characterizing Sea Clutter Properties and Training Sample Selection by Wenhao Chen, Yong Zou, Zhengzhou Li, Shengrong Zhong, Haolin Gan, Aoran Li

“…These achievements highlight the importance of accurate sea clutter modeling and optimal training sample selection in improving target detection performance and ensuring the reliability of radar-based maritime surveillance.…”
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Multi objective optimization and experimental investigation of the stirring performance of a novel micro actuator by Zhuowei He, Junjie Lei, Jingjing Yang, Huba Zhu

“…Subsequently, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized for Multi-Objective Optimization to identify the optimal combination of structural parameters. …”
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RFID‐Based Enhanced Resource Optimization for 5G/6G Network Applications by Stella N. Arinze, Augustine O. Nwajana

“…These gains highlight the effectiveness of the RFID‐based optimization model in meeting the stringent performance requirements of 5G networks, particularly in high‐density deployments. …”
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Distributed energy storage hierarchical partition dispatch control of virtual power plant based on SaDE-BBO algorithm by Tianyi Yu, Shijia Wei, Tao Lu, Zhipeng Zhang, Ning Sun

“…This method is based on the operation structure of the virtual power plant, analyzes the operating characteristics of the distributed energy storage system and the output of uncertainty factors, considers the grid load, renewable energy and distributed energy storage on the time scale, and constructs hierarchical partitions of the virtual power plant. The dispatch model determines the day-ahead and day-in-day hierarchical partition dispatch control objective functions, and sets corresponding constraints; the dispatch control model based on the solution of the SaDE-BBO algorithm outputs the virtual power plant distributed energy storage hierarchical partition dispatch control optimization plan. …”
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Source-storage-load optimization control technology of DC microgrid with virtual energy storage by WANG Chang, JIANG Yu, FU Shouqiang, SHU Yinan, ZHANG Xiangyu

“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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Probabilistic Optimization Method for Pilot-Bus Selection and Network Partitioning of AC/DC System by Wei YAN, Biao YANG, Jingshan MO, Youbin ZHOU, Tao WANG, Fan XIAO

“…With consideration of the reactive power partitioning balance demand under the node power variation of source-load-converter station, an optimization model is established considering the controllability of the coupling bus of AC/DC system, and is solved by the immune genetic algorithm. …”
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Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning by Yizhe Wang, Xiaoguang Yang, Yangdong Liu, Hailun Liang

“…Based on the three key parameters of cycle, arterial coordination offset, and green split, a set of hierarchical control algorithms based on reinforcement learning is constructed to optimize and improve the current signal timing scheme. …”
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Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu, Mingyue Shi

“…Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. …”
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Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Com... by L. E. Simms, N. Yu. Ganushkina, M. Van derKamp, M. Balikhin, M. W. Liemohn

“…Logistic regression models were improved by the addition of multiplicative interaction and quadratic terms. …”
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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…This study proposes an improved YOLOv11 model to address the limitations of traditional tomato recognition algorithms in complex agricultural environments, such as lighting changes, occlusion, scale variations, and complex backgrounds. …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…This study designs a building energy supply system integrating PVT and a water-loop heat pump based on Tianjin's meteorological data, using TRNSYS software to establish a dynamic model. By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. …”
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Application of Deep Learning for Stock Prediction Within the Framework of Portfolio Optimization in Quantitative Trading by Xiaoyu Qin

“… This paper proposes a method for stock prediction and portfolio optimization as a part of quantitative trading based on a combination of Bi-RNN and a modified snake optimization algorithm (MSOA) to build optimal portfolios and outperform conventional models and benchmarks. …”
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