Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

“…Subsequently, the Sparrow Optimization Algorithm (SSA) is applied to optimize the hyperparameters of the ResNet50 model, which is trained on DGA data as the teacher model. …”
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Human footprint with machine learning identifies risks of the invasive weed Conyza sumatrensis across land-use types under climate change by Hua Cheng, Kasper Johansen, Baocheng Jin, Shiqin Xu, Xuechun Zhao, Liqin Han, Matthew F. McCabe

“…This study compares the predictive performance of 10 machine learning algorithms, including random forests, maximum entropy, support vector machines, and others, by integrating global occurrence records with climatic, edaphic, and human activity variables to identify the most robust model for predicting the global distribution of the invasive weed, Conyza sumatrensis (Retz.) …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…A validated CFD model generated 935 numerical cases across diverse operational and design parameters, which were used to train and evaluate three machine learning algorithms: linear regression (LR), support vector regression (SVR), and artificial neural networks (ANN). …”
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Data Decomposition Modeling Based on Improved Dung Beetle Optimization Algorithm for Wind Power Prediction by Jiajian Ke, Tian Chen

“…To enhance prediction accuracy, this paper presents a hybrid wind power prediction model that integrates the improved complementary ensemble empirical mode decomposition (ICEEMDAN), the RIME optimization algorithm (RIME), sample entropy (SE), the improved dung beetle optimization (IDBO) algorithm, the bidirectional long short-term memory (BiLSTM) network, and multi-head attention (MHA). …”
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DRaCOon: a novel algorithm for pathway-level differential co-expression analysis in transcriptomics by Fernando M. Delgado-Chaves, Ferdinand Spurny, Tanja Laske, Mhaned Oubounyt, Jan Baumbach

“…However, a key challenge is the lack of robust methods and benchmarks specifically for evaluating algorithms’ ability to identify disrupted gene-gene associations across conditions. …”
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Improved adaptive FPGA dark channel prior dehazing algorithm for edge applications in agricultural scenarios by Qunpeng Gao, Baiquan Qian, Fengqi Yu, Liye Chen, Peng Gao, Jiatao Wu, Zonghong Li, Weixing Wang, C.V. Jiaxing Xie

“…The experimental results show that the optimized algorithm maintains superior dehazing quality (outperforming other dehazing algorithms in the field on metrics including PSNR, SSIM, and information entropy).…”
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Pattern Recognition in Urban Maps Based on Graph Structures by Xiaomin Lu, Zhiyi Zhang, Haoran Song, Haowen Yan

“…While both have achieved certain recognition outcomes, they suffer from four key limitations: (1) insufficient algorithmic interpretability; (2) limited model generalizability; (3) restricted pattern diversity in recognition; (4) inability of existing methods (including deep learning and traditional algorithms) to achieve multi-pattern recognition across heterogeneous map group types (e.g., building groups vs. road networks) using a single framework. …”
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Adaptive deep feature representation learning for cross-subject EEG decoding by Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang

“…Conclusions: The promising results highlight the effectiveness of the ADFR algorithm for EEG decoding and show its potential for practical applications.…”
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A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

“…The key findings of this research are as follows: • Differential Entropy and Higuchi’s Fractal Dimension proved effective in capturing emotional brain dynamics • XGBoost outperformed other classifiers in both DEAP and SEED datasets • The proposed method demonstrates robustness across subject variations and datasets…”
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Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Within this framework, the Soft Actor-Critic (SAC) algorithm is employed to construct a policy optimization mechanism. …”
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Finding Key Nodes in Complex Networks Through Quantum Deep Reinforcement Learning by Juechan Xiong, Xiao-Long Ren, Linyuan Lü

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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

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Different environmental factors predict the occurrence of tick-borne encephalitis virus (TBEV) and reveal new potential risk areas across Europe via geospatial models by Patrick H. Kelly, Rob Kwark, Harrison M. Marick, Julie Davis, James H. Stark, Harish Madhava, Gerhard Dobler, Jennifer C. Moïsi

“…To better define TBE hazard risks and elucidate regional-specific environmental factors that drive TBEV circulation, we developed two machine-learning (ML) algorithms to predict the habitat suitability (maximum entropy), and occurrence of TBEV (extreme gradient boosting) within distinct European regions (Central Europe, Nordics, and Baltics) using local variables of climate, habitat, topography, and animal hosts and reservoirs. …”
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Analytical and Geometric Foundations and Modern Applications of Kinetic Equations and Optimal Transport by Cécile Barbachoux, Joseph Kouneiher

“…Our framework is further applied to the study of hydrodynamic limits, collisional relaxation in magnetized plasmas, the Vlasov–Poisson system, and modern data-driven algorithms, highlighting the central role of entropy as both a physical and variational tool across disciplines. …”
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Simulation-Based Two-Stage Scheduling Optimization Method for Carrier-Based Aircraft Launch and Departure Operations by Jue Liu, Nengjian Wang

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Pumping up your predictive power for cognitive state detection with the proper GAINS by Victoria Ribeiro Rodrigues, Jeremy R. Prieto, Szilard L. Beres, Chad Stephens, Christopher Myers, Nicholas J. Napoli

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Wide Bandwidth Inverse Synthetic Aperture Radar Imaging and Cross-Range Scaling via Modified Polar Format Algorithm by Rongzhen Du, Lei Liu, Yinyin Jiang, Xiangyong Cao, Xueru Bai, Feng Zhou

“…By applying the minimum entropy criterion, the algorithm iteratively refines and optimizes the estimation of these parameters, compensating for all MTRC and phase errors in a single step, thus ensuring high overall compensation accuracy. …”
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Research on multi-algorithm and explainable AI techniques for predictive modeling of acute spinal cord injury using multimodal data by Jiaojiao Tai, Linbang Wang, Yijun Xie, Yang Li, Hua Fu, Xiaowen Ma, Haiyan Li, Xinying Li, Ziqiang Yan, Jingkun Liu

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Decoding Colon Cancer Heterogeneity Through Integrated miRNA–Gene Network Analysis by Qingcai He, Zhilong Mi, Tianyue Liu, Taihang Huang, Mao Li, Binghui Guo, Zhiming Zheng

“…This study establishes a multi-dimensional stratification framework through integrative analysis of miRNA–gene co-expression networks, employing the MRNETB algorithm coupled with Markov flow entropy (MFE) centrality quantification. …”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

“…In recent years, the continuous advancement of digital technologies such as telemedicine and medical cloud computing has promoted collaborative research and diagnosis across multiple medical centers. However, the timely remote transmission and analysis of large volumetric medical images still pose significant challenges. …”
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