Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…Moreover, forecast values of sweep force at the current moment help formulate the dispatch plan for the cleaning mechanism in the next moment, thus ensuring precise control of the physical model. The Improved Whale Optimization Algorithm (IWOA) is employed to optimize parameters in this blueprint, facilitating real-time scheduling by rapidly converging to the global optimum. …”
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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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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…Subsequently, six machine learning (ML) models were developed and compared to identify the optimal model. …”
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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

“…A hybrid Particle Swarm Optimization-Gray Wolf Optimization (PSO-GWO) algorithm is proposed to obtain optimal solutions. …”
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The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

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Optimization of Analog Circuit Parameters Using Bidirectional Long Short-Term Memory Coupled with an Enhanced Whale Optimization Algorithm by Hengfei Yang, Shiyuan Yang, Debiao Meng, Chenghao Hu, Chaosheng Wu, Bo Yang, Peng Nie, Yuan Si, Xiaoyan Su

“…However, the training of BiLSTM involves the adjustment of multiple hyperparameters (such as the number of layers, the number of hidden units, and the learning rate), which complicates the training process of the model. To enhance the efficiency and accuracy of neural network model development, this study proposes an Improved Whale Optimization Algorithm-assisted BiLSTM establishment strategy (IWOA-BiLSTM). …”
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Evolutionary Algorithms for the Optimal Design of Robotic Cells: A Dual Approximation for Space and Time by Raúl-Alberto Sánchez-Sosa, Ernesto Chavero-Navarrete

“…Through simulations and a digital model of the cell, key metrics such as total space reduction, operational time improvement, and productivity increase are evaluated. …”
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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…Data preprocessing, including Z-score normalization and Independent Component Analysis (ICA), ensures feature scaling and dimensionality reduction for improved model performance, enabling effective optimization. …”
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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

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PCA-Kriging-Based Oscillating Jet Actuator Optimization and Wing Separation Flow Control by Qixiang Sun, Wanbo Wang, Jiaxin Pan

“…The optimization objectives are to improve the sweeping uniformity and range of the jet. …”
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An Algorithm of Train Operation Environment Recognition Based onEmbedded GPU Platform by XIONG Minjun, LI Chen, ZHANG Huiyuan, PENG Liantie, SU Zhen

“…The instance segmentation network MaskRCNN based on deep learning is improved and trained, and the model is accelerated based on TensorRT. …”
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Heat Pump Temperature Trajectory Planning Algorithm for Bus Voltage Sag Suppression by Yangyang ZHAO, Lan LIU, Wei ZHAO, Shuang ZENG, Anqi LIANG, Hanqiu WANG, Kai MA

“…The simulation results show that the proposed algorithm can significantly suppress the transient sag of DC bus voltage in the process of heat pump temperature regulation, which are well suited to the smooth control and improving stability of building’s DC microgrid system.…”
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Coordinated multi-objective optimization scheduling for electric vehicle swapping station cluster and grid by Xiang Liao, Ziyu Zheng, Beibei Qian, Haiwei Wang, Dianling Zhan, Junyi Shi, Chaoshun Li, Wei Huang

“…Meanwhile, an electricity mutual assistance strategy between EVBESS is proposed to improve overall energy efficiency. Subsequently, an improved many-objective optimization algorithm based on multiple update strategies (G-MOMUS) is used to solve the model. …”
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PSO-NMPC control strategy based path tracking control of mining LHD (scraper) by Ya Liu, Ping-an Peng, Li-guan Wang, Jia-xi Wu, Ming-yu Lei, Chao-wei Zhang, Ru Lei

“…To address these issues, this paper proposes a PSO-NMPC control strategy that integrates a particle swarm optimization algorithm (PSO) into the NMPC controller to enhance path tracking for LHDs. …”
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A Comparative Study of Customized Algorithms for Anomaly Detection in Industry-Specific Power Data by Minsung Jung, Hyeonseok Jang, Woohyeon Kwon, Jiyun Seo, Suna Park, Beomdo Park, Junseong Park, Donggeon Yu, Sangkeum Lee

“…This study compares and analyzes statistical, machine learning, and deep learning outlier-detection methods on real power-usage data from the metal, food, and chemical industries to propose the optimal model for improving energy-consumption efficiency. …”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…The research constructs a mathematical model with multiple objective constraints, accurately identifies the adaptation shortcomings of the existing system in dynamic scenarios, and then employs a Biogeography-Based Optimization (BBO) algorithm for global optimization of control parameters. …”
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Multi-objective optimization of grinding process parameters for complicated worm space surface based on the grey wolf optimization algorithm by Jiongkang Ren, Shisong Wang, Keqi Ren

“…To account for actual working conditions, we developed constrained models for grinding ratio and machining rigidity and improved the boundary processing method for MOGWO optimization. …”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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Fault Diagnosis Method for Transformer Winding Based on Differentiated M-Training Classification Optimized by White Shark Optimization Algorithm by Guochao Qian, Kun Yang, Jin Hu, Hongwen Liu, Shun He, Dexu Zou, Weiju Dai, Haozhou Wang, Dongyang Wang

“…The principal contributions are threefold: First, building upon the fundamental principles of the M-training algorithm, we establish a classification model incorporating diversified classifiers. …”
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