Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning by Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Somaye Mohammadi, Len Gelman

“…An innovative algorithm is also introduced to identify resonance regions for optimal filter selection in envelope analysis, improving fault-related feature extraction and reducing noise. …”
Get full text

Short-Term Power Prediction for Wind Farm and Solar Plant Clusters Based on Machine Learning Method by Yang CUI, Zhenghong CHEN, Peihua XU

“…Firstly, the machine learning-based Bisecting K-Means(BKM) clustering algorithm is used to reasonably divide the wind farms and PV stations in the region into clusters; Secondly, based on the correlation between of the historical power data of each power station and the total historical power data in the region, a representative power station is selected for each region; Thirdly, after optimizing and correcting the NWP(numerical weather prediction) model of each representative power station, a short-term power prediction framework model is established using BP neural network based on the cluster division of wind farms and PV power plants. …”
Get full text

Three-dimensional image-guided navigation technique for femoral artery puncture by Yunmeng Zhang, Shenglin Liu, Qiang Zhang, Qingmin Feng

“…An improved ICP method is implemented to optimize surface point cloud alignment, providing higher efficiency and accuracy compared to conventional approaches. …”
Get full text

Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…The DE algorithm works by seeking the best solution in a complex parameter space through iterations and performance evaluations, thereby significantly enhancing the performance of the forecasting model. …”
Get full text

A Machine Learning Approach to Analyze Manpower Sleep Disorder by Reza Amiri

“…Moreover, a combination of machine learning and metaheuristic algorithms such as eXtreme Gradient Boosting and particle swarm optimization are used to make an accurate predictive model. …”
Get full text

Cache Assignment for a Flexible Mobile User in Wireless Heterogeneous Networks by Mohammad Hossein Amerimehr, Parisa Eslami, Nahid Amani, sara Efazati

“…We exploit this property to provide an efficient approximate solution (i.e., a greedy algorithm) that is guaranteed to perform within a constant of  as well as the optimal solution. …”
Get full text

NMPC-Based 3D Path Tracking of a Bioinspired Foot-Wing Amphibious Robot by Heqiang Cao, Hailong Wang, Zhiqiang Hu

“…To this end, a nonlinear model predictive control (NMPC) algorithm is employed to compute optimal control inputs, as it effectively addresses the challenges of strong nonlinearity, coupling effects, and multi-objective optimization. …”
Get full text

User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
Get full text

ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…In summary, the ST-YOLOv8 model, by integrating advanced neural network architectures and optimization techniques, significantly improves detection accuracy and reduces false detection rates. …”
Get full text

REU-Net: A Remote Sensing Image Building Segmentation Network Based on Residual Structure and the Edge Enhancement Attention Module by Tianen Yuan, Bo Hu

“…Furthermore, a hybrid loss function combining edge consistency loss and binary cross-entropy loss is used to train the network, aiming to improve segmentation accuracy. Experimental results show that REU-Net(2EEAM) achieves optimal performance across multiple evaluation metrics (such as P, MPA, MIoU, and FWIoU), particularly excelling in the accurate recognition of building edges, significantly outperforming other network models. …”
Get full text

Distribution-Based Approach for Efficient Storage and Indexing of Massive Infrared Hyperspectral Sounding Data by Han Li, Mingjian Gu, Guang Shi, Yong Hu, Mengzhen Xie

“…Additionally, it optimizes the rowkey design using the BPDS model, thereby enabling the distributed storage of data in HBase. …”
Get full text

The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…GRIPP significantly improved emission identification and pathway representativeness compared to traditional backtracking methods by exploring multiple potential particle origins and optimizing seeding parameters. …”
Get full text

Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…Decision tree (DT), gradient boosting tree (GBT), Naïve Bayes (NB), and random forest (RF) algorithms are used to determine the best model. The comparative analysis of ML algorithms revealed that the GBT algorithm exhibits superior predictive capabilities regarding HPPT bench failure predictions. …”
Get full text

A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning by Xin Huang, Rongwu Xu, Ruibiao Li

“…However, the labeled data available for the training of URN prediction model is limited. Semi-supervised learning (SSL) can improve the model performance by using unlabeled data in the case of a lack of labeled data. …”
Get full text

Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
Get full text

Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning by Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang

“…The soft-voting ensemble algorithm achieved an optimal predictive performance with an AUC of 0.839 (95% CI 0.786–0.889) for the all-features model, while logistic regression using common features achieved an AUC of 0.767 (95% CI 0.704–0.825), outperforming ROX and mROX indices. …”
Get full text

Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
Get full text

Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
Get full text

Boundary Guidance Strategy and Method for Urban Traffic Congestion Region Management in Internet of Vehicles Environment by Chuanxiang Ren, Zhen Wang, Changchang Yin, Hui Xu, Li Wang, Luyao Guo, Juntao Li

“…Meanwhile, a method for the boundary guidance strategy is presented in which the macroscopic fundamental diagram (MFD) is used to determine the optimal accumulation, a traffic flow equilibrium model is established to calculate the real-time accumulation, and a fuzzy adaptive PID control algorithm is designed to calculate the optimal traffic inflow of the traffic congestion region. …”
Get full text

Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…Adopting Machine Learning (ML) models for donor–recipient matching can potentially improve kidney allocation processes when compared with traditional points-based systems. (2) Methods: This study developed an ML-based approach for donor–recipient matching. …”
Get full text