A Hybrid CT-DEWCA-Based Energy-Efficient Routing Protocol for Data and Storage Nodes in Underwater Acoustic Sensor Networks by Imran Khan, Muhammad Rauf, Atif Jamil

“…This model enhances node placement by implementing a “strategic dual transmission” approach, which employs CT for short-distance data transfer and utilizes the DEWCA hybrid algorithm to select optimal relay nodes for long-distance communication. …”
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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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Research on a Hierarchical Control Strategy for Anti-Lock Braking Systems Based on Active Disturbance Rejection Control (ADRC) by Shi Luo, Bing Zhang, Jiantao Ma, Xinyue Zheng

“…Firstly, a vehicle dynamics model and an ABS model based on the EMB system are established; secondly, a speed observer based on the dilated state observer is used in the upper layer to design a pavement recognition algorithm, which recognizes the current pavement and outputs the optimal slip rate; then, an ABS controller based on the ADRC algorithm is designed for the lower layer to track the optimal slip rate. …”
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A Non-invasive Load Recognition Approach Incorporating SENet Attention Mechanism and GA-CNN by Xin SHEN, Gang WANG, Yitao ZHAO, Zhao LUO, Zhao LI, Xiaohua YANG

“…Secondly, the U-I trajectory map of the residential load is extracted and weighted pixelated to obtain the WVI (Weighted pixelated VI) feature matrix through computation, which is applied as the feature coefficient to train the SENet-CNN model. Finally, by virtue of the genetic algorithm, the SENet-CNN model is trained and the hyperparameters of the CNN-SENet model are optimized to improve the model load recognition performance and computational efficiency. …”
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A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

“…Introduce SIoU instead of the original loss function to accelerate model convergence. Finally, the introduction of the Ghost module to optimize the backbone network can reduce the computational and parametric quantities of the model without losing the model performance, improve the detection speed, and make the model easier to be deployed on resource-constrained devices. …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Therefore, this paper proposes a financial fraud detection model based on Stacking ensemble learning algorithm, which integrates many basic learners such as logical regression (LR), decision tree (DT), random forest (RF), Gradient Boosting Tree (GBT), support vector machine (SVM) and neural network (NN), and introduces feature importance weighting and dynamic weight adjustment mechanism to improve the model performance. …”
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Research on an Intelligent Prediction Method for the Carbon Emissions of Prefabricated Buildings During the Construction Stage, Based on Modular Quantification by Yang Yang, Xiaodong Cai, Xinlong Ma, Gang Yao, Ting Lei, Hongbo Tan, Ying Wang

“…Based on the machine learning algorithm, a carbon emissions prediction model for prefabricated buildings’ construction stage was established and hyperparameter optimization was conducted. …”
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Comprehensive Evaluation and Trade‐Off of Top‐Level Requirements for BWB UAVs by Xinshi Suo, Zhouwei Fan, Yundong Guo, Tengzhou Xu

“…Four critical criteria—cost‐effectiveness, payload capacity, flight performance, and stealth capability—are applied to identify seven representative top‐level requirements, which are subsequently integrated into a comprehensive evaluation model. A parallelizable subset‐simulation optimization algorithm is implemented to iteratively refine the design, thereby maximizing overall system competitiveness. …”
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Research Progress of Finite Element Technology in Wood Processing by Maosen Wang, Lin Yang

“…It highlights challenges such as model accuracy and algorithm optimization, suggesting that continuous improvements in FEA models and algorithms can further enhance processing efficiency and product quality. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…The algorithm improves prediction power through progressive convergence. …”
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Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. …”
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Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN by Lei Chen, Jun Wang, Zhang Sun, Tao Huang, Fan Wu

“…Furthermore, in order to overcome the drawback that too frequent conversion of unit operating mode would reduce the service life and smoothing effect of the VSPSS unit, the optimization model of the base power of the VSPSS is established and solved by the grid adaptive direct search method (MADS) to obtain the control signal of the VSPSS for suppressing the short-term fluctuations of the PV output. …”
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Research on wind temperature prediction of tunneling working site based on PSO−SVR by Yanhe LI, Zhijun WAN, Zhenzi YU, Hong GOU, Wanli ZHAO, Jiale ZHOU, Peng SHI, Zheng ZHEN, Yuan ZHANG

“…So PSO optimization model parameters play an important role in improving SVR fitting degree, generalization and prediction accuracy. …”
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Enhancement Ear-based Biometric System Using a Modified AdaBoost Method by Abdulkareem Merhej Radhi, Subhi Aswad Mohammed

“…The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. …”
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MC64-ClustalWP2: a highly-parallel hybrid strategy to align multiple sequences in many-core architectures. by David Díaz, Francisco J Esteban, Pilar Hernández, Juan Antonio Caballero, Antonio Guevara, Gabriel Dorado, Sergio Gálvez

“…The new parallelization approach has focused into the most time-consuming stages of this algorithm. In particular, the so-called progressive alignment has drastically improved the performance, due to a fine-grained approach where the forward and backward loops were unrolled and parallelized. …”
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Application of federated learning in predicting breast cancer by Chai Jiarui

“…Subsequently, each participant then sends the updated model parameters to the central server, where the FedAvg algorithm combines them to produce a global model. …”
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BedEye: A Bed Exit and Bedside Fall Warning System Based on Skeleton Recognition Technology for Elderly Patients by Liang-Bi Chen, Wan-Jung Chang, Tzu-Chin Yang

“…The proposed BedEye system innovatively utilizes OpenPose-light, which is a lightweight version of the OpenPose model optimized for edge computing. The proposed BedEye system processes real-time images captured by an RGB sensor, which are then fed into a deep learning model running locally on an Nvidia Jetson Xavier-NX edge computing device. …”
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Research on the Impact of Partial Shading on Large-scale by CHENG Yuxu, LI Jianquan, WU Xiaoyun, ZHAI Wenjie

“…With simulation, it analyzed the limitations of traditional single channel, single peak MPPT tracking algorithm in partial shading applications, proposed several measures to improve the performance against partial shading of PV arrays. …”
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Advanced time-series InSAR analysis to estimate surface deformation and utilization of hybrid deep learning for susceptibility mapping in the Jakarta metropolitan region by Wahyu Luqmanul Hakim, Muhammad Fulki Fadhillah, Joong-Sun Won, Yu-Chul Park, Chang-Wook Lee

“…The performance of these hybrid models will be compared to that of standalone CNN and LSTM algorithms as the base model before parameter optimization. …”
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Bioregionalization analyses with the bioregion R package by Pierre Denelle, Boris Leroy, Maxime Lenormand

“…The recent emergence of global databases, improvements in computational power and the development of clustering algorithms coming from the network theory have led to several major updates of the bioregionalizations of many taxa. …”
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