Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…Achievements: the signal-to-noise ratio can be effectively improved to 77.8 by using the wavelet denoising, and the parameter modeling optimized by the GWO algorithm can significantly improve the prediction accuracy, with an increase of about 3%–5%. …”
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Cognitive MIMO radar waveform design for multiple moving extended targets by SHEN Tingli, ZHANG Yunlei, LU Jianbin, YU Guohua

“…In order to solve the problem of boosting cognitive MIMO radar for multiple moving target detection in cluttered backgrounds, this paper constructs a multi-target optimization model based on the dual mutual information criterion, takes into account the problem of linear variation of the motion target impulse response (TIR), estimates the TIR at the next moment by using Kalman filtering algorithm. …”
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Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System by Guo Tong, Wang Jiawen, Liang Yingnan, Peng Buyu, Liu Tao, Liu Yiqun

“…Through mathematical models and computer simulations, it is the current mainstream optimization direction to optimize the structure of the boom linkage mechanism and improve its strength and stability. …”
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3D craniofacial registration using thin-plate spline transform and cylindrical surface projection. by Yucong Chen, Junli Zhao, Qingqiong Deng, Fuqing Duan

“…First, the gradient descent optimization is utilized to improve a cylindrical surface fitting (CSF) for the reference craniofacial model. …”
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Broad learning system based on attention mechanism and tracking differentiator by LIAO Lüchao, ZOU Weidong, YANG Jialong, LU Huihuang, XIA Yuanqing, GAO Jianlei

“…To alleviate these problems, broad learning system based on attention mechanism and tracking differentiator (TD), abbreviated as A-TD-BLS, was proposed. In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…Validation employed the Gamma Technologies Suite simulation platform and the Next Generation Simulation dataset, with benchmark comparisons against Equivalent Consumption Minimization Strategy, Fuzzy Logic Control, and Thermostat Strategy models.ResultsThe optimized Proximal Policy Optimization algorithm achieved 93.2% accuracy and 1.0% loss rate upon convergence, with an average feedback time of 32 milliseconds. …”
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Research on caching strategy based on transmission delay in Cell-Free massive MIMO systems by Rui WANG, Min SHEN, Yun HE, Xiangyan LIU

“…To meet the ultra-low latency and ultra-high reliability requirements of users in the future mobile Internet， the wireless caching technology was combined with Cell-Free massive MIMO systems.The caching model was designed based on AP cooperative caching and regional popularity evaluation.The transmission delay expression involving AP clustering， cooperative caching， and regional popularity was derived， and the content placement problem was expressed as total content transmission delay minimization.Through the demonstration of the NP-hard and submodular monotony of the optimization problem， the greedy algorithm-based optimization strategy was proposed.Simulation results show that the proposed strategy can effectively reduce the content transmission delay and improve the cache hit rate.…”
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Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

“…To maximize the library of image features within the dictionary matrix, an optimal model was established for X-ray SDR images of welds based on orthogonal optimization, along with a dictionary matrix solving algorithm featuring orthogonal optimization. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…The choice to prioritize thermal and visual imaging above mathematical modeling or optimization algorithms arises from the necessity of delivering practical, scalable inspection solutions that can be readily implemented in the field. …”
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Soft Measurement of Wastewater Treatment System Based on PSOGA-WNN by LIU Yuhui, MAI Wenjie, LI Xiaoyong, ZHAO Yinzhong, HE Xinzhong, HUANG Mingzhi

“…To accurately predict the SS_eff (effluent SS) content and COD_eff (effluent COD) concentration in water quality parameters and further improve the water quality early warning mechanism,this paper proposes the PSOGA-WNN soft measurement model of paper wastewater effluent quality to obtain the main water quality technical parameters,COD_inf (influent COD),Q (influent flow),pH (influent pH),SS_inf (influent SS),T (influent temperature),DO (influent dissolved oxygen),COD_eff,and SS_eff, for predicting the quality of wastewater from the wastewater treatment plant.Among them,the prediction results of PSOGA-WNN are compared with the neural networks of PSO-WNN,GA-WNN,and PSOGA-BP.The results show that the PSOGA-WNN neural network has the highest prediction accuracy,which indicates that the PSOGA hybrid parameter optimization algorithm based on the genetic algorithm and particle swarm algorithm has obvious superiority in optimizing the prediction accuracy of the model.The WNN neural network has certain advantages over BP neural network in terms of fitting degree as well as error accuracy and is an effective means of simulation prediction.…”
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An Adaptive Weight Physics-Informed Neural Network for Vortex-Induced Vibration Problems by Ping Zhu, Zhonglin Liu, Ziqing Xu, Junxue Lv

“…In this study, a VIV dataset of a cylindrical body with different degrees of freedom is used to compare the performance of the PINN and three PINN optimization algorithms. The findings suggest that, compared to a standard PINN, the AW-PINN lowers the mean squared error (MSE) on the test set by 50%, significantly improving the prediction accuracy. …”
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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…Then, the BP neural network is improved by using particle swarm optimization (PSO) combined with the simulated annealing algorithm. …”
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Reoptimization Heuristic for the Capacitated Vehicle Routing Problem by Rodrigo Linfati, John Willmer Escobar

“…Next, the local search procedure is executed to improve the solution. A classic optimization is performed on all instances using the original and new customers’ information for later comparison to minimize distance. …”
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Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks by Van-Dinh Nguyen, Chuyen T. Nguyen, Oh-Soon Shin

“…We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. …”
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Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information. by Zhengwen Shen, Zhengwen Shen, Huafeng Wang, Weiwen Xi, Xiaogang Deng, Jin Chen, Yu Zhang

“…In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. …”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Next, Star Blocks from the StarNet framework are employed to optimize the C3k2 module in the Neck stage, thereby improving the localization accuracy of deep features without increasing network complexity. …”
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Core-periphery structure for district metered area partitioning in urban water distribution systems by Rair Solis Jacome, Thomaz Anchieta, Bruno M. Brentan, Manuel Herrera, Xitlali Delgado Galvan, Jose Antonio Arciniega Nevarez, Jesus Mora Rodriguez

“…The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas, applies a community structure detection algorithm conditioned by these areas, and uses an optimisation model to determine the optimal placement of boundary devices, enhancing network resilience and reducing costs. …”
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Flight Endurance Increasing Technology of New Energy UAV Based on a Strut-Braced Wing by Li Liu, Wencan Bai, Dun Yang

“…Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. …”
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Research on management mode of talent team in E-government based on big data analysis by Shixuan Hao

“…The performance analysis of the Apriori algorithm before and after improvement shows that the optimized Apriori algorithm can significantly reduce the number of scans of the data transaction database and the system running time, and the algorithm efficiency has increased by 48.26 %. …”
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