A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…The current target recognition algorithms for common maritime targets, such as buoys, reefs, other ships, and bridges of different colors, face challenges such as incomplete classification, low recognition accuracy, and a large number of model parameters. …”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

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Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives by Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao

“…We separate ProMPs as Gaussians at each timestep and minimize Kullback–Leibler (KL) divergence, with a gradient ascent–descent algorithm performed to obtain optimized ProMPs. Given optimized ProMPs, we outline a unified robot movement adaptation method for extending from a single obstacle to multiple obstacles. …”
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Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions by Guo Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang

“…Aiming to improve the treatment of multiphase pollutants, this study builds a three-objective optimization model by considering the optimization of treatment effect, energy consumption, and an innovatively constructed optimization objective of direct and indirect carbon emissions. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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Optimization of an Intelligent Music-Playing System Based on Network Communication by Liaoyan Zhang

“…The recommendation engine module in this paper is designed and optimized using Spark to implement incremental matrix decomposition on data streams, online collaborative topic model, and improved item-based collaborative filtering algorithm. …”
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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions by Carlos Rodriguez-Navarro, Francisco Portillo, Isabel Robalo, Alfredo Alcayde

“…Non-intrusive load monitoring (NILM) enables the disaggregation of appliance-level energy consumption from aggregate electrical signals, offering a scalable solution for improving efficiency. This study compared the performance of traditional NILM algorithms (Mean, CO, Hart85, FHMM) and deep neural network-based approaches (DAE, RNN, Seq2Point, Seq2Seq, WindowGRU) under various experimental conditions. …”
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Design of a High-Efficiency External Rotor Interior Permanent Magnet Synchronous Motor Without Magnetic Leakage Flux Path by Kyoung-Soo Cha, Jae-Hyun Kim, Soo-Gyung Lee, Min-Ro Park

“…A V-shaped IPMSM is then proposed to increase the permanent magnet volume and reduce magnetic leakage. Design optimization is conducted using Gaussian process models (GPMs) constructed with a Latin hypercube design (LHD), and the optimal design is determined using a gradient descent algorithm. …”
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USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…To address these issues, we propose a specialized algorithm named Unmanned-system Small-object Detection-You Only Look Once (USD-YOLO). …”
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Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway by Wenliang Zhou, Junli Tian, Jin Qin, Lianbo Deng, TangJian Wei

“…And its heuristic algorithm is designed to optimize the multiperiod mixed train schedule beginning with generating an initial solution by scheduling all types of train type by type and then repeatedly improving their periodic schedules until the objective value cannot be reduced or the iteration number reaches its maximum. …”
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Evaluation and Optimization of Air Traffic Complexity Based on Resilience Metrics by Hongyong Wang, Jiawen Huang, Taotao Deng, Ziqi Song

“…By establishing a sector complexity optimization model, the complexity of sector air traffic and its volatility can be greatly reduced by changing the departure time of some flights. …”
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Enhancing mass vaccination programs with queueing theory and spatial optimization by Sherrie Xie, Maria Rieders, Srisa Changolkar, Bhaswar B. Bhattacharya, Elvis W. Diaz, Michael Z. Levy, Michael Z. Levy, Ricardo Castillo-Neyra, Ricardo Castillo-Neyra

“…Queueing theory offers a framework for modeling queue formation at vaccination sites and its effect on vaccine uptake.MethodsWe developed an algorithm that integrates queueing theory within a spatial optimization framework to optimize the placement of mass vaccination sites. …”
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An Improved UNet-Based Path Recognition Method in Low-Light Environments by Wei Zhong, Wanting Yang, Junhuan Zhu, Weidong Jia, Xiang Dong, Mingxiong Ou

“…The optimal attention mechanism is incorporated into the optimized network to enhance the model’s ability to detect path edges and improve detection performance. …”
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Cooperative trajectory optimization for multiple connected vehicles at an unsignalized intersection by Hao Yang, Xianyang Li, Duoyang Qiu, Xiaomeng Zhu

“…Through numerical simulation analysis of intersection scenarios including crossroad and roundabout, the results demonstrate that the proposed algorithm can achieve optimal trajectories for multi-vehicle cooperative motion while ensuring safe vehicle operation, which improves the efficiency of future intelligent traffic networks.…”
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A Multi-Objective Bio-Inspired Optimization for Voice Disorders Detection: A Comparative Study by Maria Habib, Victor Vicente-Palacios, Pablo García-Sánchez

“…The optimization problem has been formulated as a wrapper-based algorithm for feature selection and multi-objective optimization relying on four machine learning algorithms: K-Nearest Neighbour algorithm (KNN), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM). …”
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Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…The developed sigmoid (SG) activation function-based ELM (SG-ELM) shows performance improvement over sine (SI) function-based ELM (SI-ELM) model and PS-SVR model with an improvement of 79.25 % and 89.4 % using root mean square error (RMSE) performance measuring parameter. …”
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Novel Design and Optimization of Porous Titanium Structure for Mandibular Reconstruction by Renshun Liu, Yuxiong Su, Weifa Yang, Xiaobing Dang, Chunyu Zhang, Ruxu Du, Yong Zhong

“…The design and optimization technique of the porous structure presented in this paper can be used to control peak stress, improve porosity, and fabricate a lightweight scaffold, which provides a potential solution for mandibular reconstruction.…”
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Dynamic optimization of intersatellite link assignment based on reinforcement learning by Weiwu Ren, Jialin Zhu, Hui Qi, Ligang Cong, Xiaoqiang Di

“…Different from the swarm intelligence method in principle, this algorithm models the combinatorial optimization problem of links as the optimal sequence decision problem of a series of link selection actions. …”
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