Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis by Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang

“…Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. …”
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers by Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura, Shingo Numata, Takafumi Mochizuki, Keijiro Kubota, Masaki Yasukawa, Toshihiro Nemoto, Toshio Koike

“…This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…And optimize the network structure through channel pruning technology to improve model lightweighting. …”
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ECMS-Based MPC Strategy for Multi-Mode Hybrid Electric Trucks by Longjian Li, Changqing Du, Xiangyu Gongye, Jinhai Wang

“…To address the adaptive energy management optimization challenge of a hybrid powertrain system consisting of an internal combustion engine and dual electric motors, an Equivalent Consumption Minimization Strategy (ECMS) is introduced into the Model Predictive Control (MPC) framework. …”
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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

“…The voting system and the dynamic SelectOut algorithms improve the convergence of the FL model and successfully handle the difficulties presented by uneven and heterogeneous datasets. …”
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A Precise Oxide Film Thickness Measurement Method Based on Swept Frequency and Transmission Cable Impedance Correction by Yifan Li, Qi Xiao, Lisha Peng, Songling Huang, Chaofeng Ye

“…A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. …”
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Continuous Action Air Combat Maneuver Decision-Making Based on T-MGMM by Junzhe Jiang, Hongming Wang, Zhixing Huang, Zhuangfeng Zhou, Xiang Wu, Wenqin Deng, Xueyun Chen

“…To address these challenges, this paper proposes a novel algorithm, T-MGMM, which integrates Transformer networks with a Multivariate Gaussian Mixture Model (MGMM). …”
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High voltage direct current system-based generation and transmission expansion planning considering reactive power management of AC and DC stations by Ehsan Akbari, Ahad Faraji Naghibi, Mehdi Veisi, Sasan Pirouzi, Sheila Safaee

“…The scheme incorporates a non-linear model. The Red Panda Optimization (RPO) is utilized to solve the provided model in order to attain a dependable and optimal solution. …”
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Frequency stabilization of a sophisticated multi-area interconnected hybrid power system considering non-inertia sources by Diaa M. Gawad, Gaber Magdy, M.A. Ebrahim, Eduard Petlenkov

“…This study accounts for various loading scenarios and system nonlinearities to validate the algorithm’s effectiveness. Furthermore, the superior performance of the RUN optimizer is verified by contrasting its results with other widely recognized optimization techniques, such as the Ant Lion optimizer (ALO) and Chernobyl disaster optimizer (CDO). …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…By establishing a multi-level classification framework that included traditional statistical models (such as ARIMA), ML models (such as SVM), deep learning (DL) models (such as CNN, LSTM), ensemble learning methods (such as AdaBoost), and hybrid models (such as the fusion architecture of intelligent optimization algorithms and neural networks), it revealed that the hybrid modelling strategy effectively improved the prediction accuracy of the model through feature combination optimization and model cascade integration. …”
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FD-GRNet: A Dendritic-Driven GRU Framework for Advanced Stock Market Prediction by Tongyan Liu, Jiayi Li, Zihang Zhang, Hang Yu, Shangce Gao

“…Comprehensive experiments on major global stock market indices demonstrate that FD-GRNet consistently outperforms several comparative algorithms across multiple evaluation metrics. Ablation studies further highlight the essential roles of FDNM and DGRNet in improving the model’s accuracy and robustness. …”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.…”
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A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…Transformer models, which are widely applied to global feature extraction, can effectively capture long-distance dependencies through the self-attention mechanism, theoretically overcoming the limitations of CNNs in global modeling. …”
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Kinematic analysis, methods and experimental studies of robot navigator movements on mecanum wheels by Sladkova L.A., Pshibiev A.M.

“…In order to verify and evaluate the effectiveness of the localization and path planning algorithm in order to improve the control system of the mobile platform on mecanum wheels, modeling and simulation of the presented model were carried out, which made it possible to assess the kinematic parameters of the platform to achieve better results. …”

Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…The improved model achieved an mAP of 83.0%, with accuracy improvements of 85.0%, 2.0%, and 5.0% compared to the baseline. …”
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STATE PREDICTION OF WIND TURBINE GENERATOR BASED ON K-CNN AND N-GRU (MT) by CHAI Tong, YUAN YiPing, MA JunYan, FAN PanPan

“…Then, to solve the problem of parameter optimization of the traditional GRU algorithm, the neural network architecture search was used to improve the GRU algorithm, and the N-GRU model was obtained. …”
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A robust multi-scale clustering framework for single-cell RNA-seq data analysis by Songrun Jiang, Chunyan Wang, Qiucheng Sun, Zhi Zhang

“…To address these challenges, we introduce a new method, single-cell Multi-Scale Clustering Framework (scMSCF), which combines multi-dimensional PCA for dimensionality reduction, K-means clustering, and a weighted ensemble meta-clustering approach, enhanced by a self-attention-driven Transformer model to optimize clustering performance. scMSCF constructs an initial clustering framework using a multi-layer dimensionality reduction strategy to establish a robust consensus on clustering structure. …”
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Dissertation council in the state scientific certification system: Organizational and management mechanisms of digital transformation by Sergey I. Pakhomov, Elena A. Loginova, Oleg V. Kulyamin, Mikhail P. Petrov

“…The integration of the electronic document management system using the platform Gosuslugi has shortened the list of required documents and reduced the timeframes for providing the service. We propose an algorithm for the transition to a registry-based model that increases the transparency and accessibility of information about dissertation councils, and identify the promising forms of council organization, including one-time councils, considering best practices of degree-awarding bodies. …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…To solve this problem, this paper proposes a hybrid method that combines multimodal data-aware attacks with Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR) agent models. By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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