Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…The results show that the combination of convolutional neural network to extract fault features and parameters to optimize the classification model structure of support vector machine can not only improve the diagnostic accuracy, but also have strong generalization performance.…”
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Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
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Application of WCA-RBF Neural Network in Fault Diagnosis of Analog Circuits by Zhiwei Jin

“…The adaptive step size was improved in the wolf pack algorithm, the parameters of the radial basis function neural network were optimized based on the wolf pack algorithm, and a wolf pack algorithm optimized radial basis function neural network model was constructed. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…The results reveal the following: (1) NTU and EER levels steadily improved from 2004 to 2022, although coordination between cities still requires enhancement; (2) CCD exhibited a temporal pattern of “progressive escalation and continuous optimization,” and a spatial pattern of “dual-core leadership and regional diffusion,” with most cities shifting from NTU-lagged to synchronized development; (3) environmental regulations (MAR) and fixed asset investment (FIX) emerged as the most influential CCD drivers, and significant nonlinear interactions were observed, particularly those involving population size (HUM); (4) CCD drivers exhibited complex spatiotemporal heterogeneity, characterized by “stage dominance—marginal variation—spatial mismatch.” …”
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Secret key generation for reconfigurable intelligent surface‐assisted MISO multi‐user system by Kexin Liu, Mingliang Li, Kaizhi Huang, Zheng Wan, Qinlong Li, Xiaoli Sun, Xiaoming Xu, Liang Jin

“…Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. …”
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Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network by Liping Yan, Yue Tang, Chan Peng, Yu Cai, Wenbo Zhang, Jing Wang

“…Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution.…”
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A Hotspot Prediction Scheme Based on Ensemble Learning With Adaptive Beamforming for Virtual Small Cell in 5G Networks by Aws Majeed Ghalib Alawadi, Hadi Seyedarabi, Reza Afrouzian, Javad Musevi Niya

“…Effectively managing network congestion in 5G systems is crucial for ensuring seamless connectivity and optimal resource utilization. In this study, an operational scheme based on hotspot prediction for Virtual Small Cell (VSC) is presented, which aims to improve coverage, reduce delay and improve energy efficiency in 5G networks for congested locations. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The classification accuracy of the combined model of this algorithm was larger at 0.925. Compared with traditional teaching methods, this approach quantitatively assesses students' technical levels and improves the relevance and scientific nature of teaching feedback.…”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…Optimization can help find a better quasi‐optimal hyperparameter combination and improve the performance of the model. …”
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. …”
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Advanced Load Balancing Based on Network Flow Approach in LTE-A Heterogeneous Network by Shucong Jia, Wenyu Li, Xiang Zhang, Yu Liu, Xinyu Gu

“…Furthermore, a novel algorithm named optimal solution-based LB (OSLB) is proposed. …”
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Mix design and performance prediction of EPS lightweight structural concrete based on orthogonal experimentation by Qianhui Zhang

“…A novel dataset was established and utilized in performance prediction using XGBoost, optimized with Seagull Optimization Algorithm (SOA), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO). …”
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…Distinct from prior DRL applications, our method rigorously couples Lyapunov-based stability guarantees with DRL-based gain tuning, ensuring formal stability despite stochastic disturbances and model uncertainties. This hybrid framework facilitates real-time optimization of control policies, contributing to improved resilience and robustness under realistic network conditions. …”
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Detection of Foreign Bodies in Transmission Line Channels Based on Fusion of Swin Transformer and YOLOv5 by XUE Ang, JIANG Enyu, ZHANG Wentao, LIN Shunfu, MI Yang

“…Finally, considering the mismatch between the real frame and the predicted frame, the structural similarity intersection over union (SIoU) is introduced to optimize the boundary errors and improve the generalization ability of the model. …”
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A Study on Vector-Based Processing and Texture Application Techniques for 3D Object Creation and Visualization by Donghwi Kang, Jeongyeon Kim, Jongchan Lee, Haeju Lee, Jihyeok Kim, Jungwon Byun

“…In this research, data weight reduction, parallel processing, and polygon simplification algorithms were applied to optimize the 3D model generation speed. …”
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Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation by Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi

“…Conclusion The study displayed the effectiveness of psychophysiology-based AI models in predicting rehabilitation engagement, thus promoting their practical application for personalized care and improved clinical health outcomes.…”
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2HR-Net VSLAM: Robust visual SLAM based on dual high-reliability feature matching in dynamic environments. by Wang Yang, Huang Chao, Zhang Yi, Tan Shuyi

“…Finally, the shared matching Siamese network with a unique dual-branch feature fusion strategy and similarity optimization algorithm is proposed to enhance the accuracy of feature matching. …”
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Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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Kinematic Calibration of Industrial Robots Based on Distance Information Using a Hybrid Identification Method by Guanbin Gao, Yuan Li, Fei Liu, Shichang Han

“…The singular value decomposition (SVD) is used to eliminate the redundant parameters of the error model. To solve the problem that traditional optimization algorithms are easily affected by data noise in high dimension identification, a novel extended Kalman filter (EKF) and regularized particle filter (RPF) hybrid identification method is presented. …”
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Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective by Yikun Su, Junhao Liu, Zhizhe Zheng

“…The optimization algorithm has been validated and shown to improve the GCPR level of the project. …”
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