Fault Detection in MV Switchgears Through Unsupervised Learning of Temperature Conditions by Grazia Iadarola, Alessandro Mingotti, Virginia Negri, Susanna Spinsante

Get full text

Artificial neural networks analysis for non-newtonian nanofluid flow with variable viscosity and MHD effects in wire covering processes by Maria Altaib Badawi, Zeeshan, Nehad Ali Shah, Imed Boukhris, Adel Thaljaoui

“…The data acquisition for the proposed ANN-LMA is generated for parameters involved in the model WCS-TGNFF through Runge-Kutta method. The training, validation, and testing phases of ANN-LMA are employed to assess the results derived from WC-TGNFF across diverse scenarios, and a comparative analysis of the derived results is conducted against a reference dataset to evaluate the precision and efficacy of the proposed ANN-LMA framework in addressing non-Newtonian fluid challenges associated with WC-TGNFF. …”
Get full text

Machine learning model for early diagnosis of breast cancer based on PiRNA expression with CA153 by Limin Niu, Weicheng Zhou, Xiao Li, Jinming Zhao, Lei Li, Xingguo Song

“…Through systematic ML optimization, we developed a stratified diagnostic model where XGBoost algorithm showed optimal performance in both training and validation cohorts for early-stage BC identification. …”
Get full text

Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

“…Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. …”
Get full text

P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…In P4CN-YOLOv5s, the Mosaic-9 and Mixup algorithms are initially used for data augmentation to augment the training dataset and enhance data complexity. …”
Get full text

Towards an intelligent integrated methodology for accurate determination of volume percentages in three-phase flow systems by Abdullah M. Iliyasu, Mohammad Sh. Daoud, Ahmed Sayed Salama, John William Grimaldo Guerrero, Kaoru Hirota

“…Further, through iterative elimination and re-evaluation, the algorithm refines the feature set, retaining only those with the highest relevance to the three-phase fluid composition. …”
Get full text

Multi-Objective Scheduling for Green Flexible Assembly Job-Shop System via Multi-Agent Deep Reinforcement Learning With Game Theory by Xiao Wang, Zhongyuan Liang, Peisi Zhong, Dongmin Li, Hongqi Li, Mei Liu

“…These datasets and a case of the plunger pump production workshop scheduling scenario are designed to analyze the basic performance of this algorithm. The results show that the proposed algorithm compares with other single-indicator optimal algorithms with 9.47 per cent, 12.66 per cent and 22.86 per cent respectively for the three-evaluation metrics (GD, and HV), which contributed to solving the practical production problem of the manufacturing industry.…”
Get full text

HAP-COVID: Hybrid Model Integrating Machine Learning and Neutrosophic Statistics to Estimate Mortality Risk in COVID-19 Comorbid Patients by Daniel Iturburu-Salvador, Lorenzo Cevallos-Torres, Rosangela Caicedo-Quiroz, Irma Naranjo-Peña, Rosa Hernández-Magallanes, Rosa Gonzáles-Quiñones

Get full text

AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification—Decoding Lateral Epicondylitis in Forearm Muscles by Mehdi Shirzadi, Mónica Rojas Martínez, Joan Francesc Alonso, Leidy Yanet Serna, Joaquim Chaler, Miguel Angel Mañanas, Hamid Reza Marateb

“…Background: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. …”
Get full text

Fusion of MHSA and Boruta for key feature selection in power system transient angle stability by WANG Man, ZHOU Xiaoyu, CHEN Fan, LAI Yening, ZHU Ying

“…The model dynamically adjusts attention weights during training, focusing on key features. Subsequently, the Boruta algorithm is employed to determine the number of key features. …”
Get full text

Penaeus vannamei aquaculture water quality prediction based on the improved back propagation neural network by DING Jinting, ZANG Zelin, HUANG Min

“…It provides a new method for the prediction and evaluation of water quality in aquaculture.…”
Get full text

YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Against the backdrop of the deep integration of national fitness and sports science, this study addresses the lack of standardized movement assessment in yoga training by proposing an intelligent analysis system that integrates an improved YOLOv11-ECA detector with the DeepSORT tracking algorithm. …”
Get full text

Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
Get full text

Civil Aircraft Landing Attitude Ultra-Limit Warning System Based on mRMR-LSTM by Fei Lu, Tong Jing, Chunsheng Xie, Haonan Chen

“…Subsequently, through data pretreatment methods such as data cleaning, frequency normalization, data standardization, and feature classification, the experimental dataset is transformed into a form recognizable by machine learning algorithms and neural network models. The necessary feature parameters are extracted to form a deep learning training dataset. …”
Get full text

Digital Industrial Design Method in Architectural Design by Machine Learning Optimization: Towards Sustainable Construction Practices of Geopolymer Concrete by Xiaoyan Wang, Yantao Zhong, Fei Zhu, Jiandong Huang

“…The models are evaluated using R², RMSE, and VAF. Various MLP architectures are explored, evaluating transfer functions and training techniques to optimize performance. …”
Get full text

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

Get full text

Slax: a composable JAX library for rapid and flexible prototyping of spiking neural networks by Thomas M Summe, Siddharth Joshi

“…To address this, we introduce Slax, a JAX-based library designed to accelerate SNN algorithm design and evaluation. Slax is compatible with the broader JAX and Flax ecosystem and provides optimized implementations of diverse training algorithms, enabling direct performance comparisons. …”
Get full text

An Inverse Modeling Multi-Objective Optimization Technique Based on Incremental Learning and Fuzzy Clustering by Gadallah Mohamed Abd Elaziz, Yasmine Abouelseoud, Sara H. Kamel

“…Extensive simulations on various benchmark problems show that the proposed algorithm drastically reduces the number of function evaluations required to reach an optimal solution compared to existing methods. …”
Get full text

Development of data driven models to accurately estimate density of fatty acid ethyl esters by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H. S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Abdolali Yarahmadi Kandahari

“…The reliability of the dataset, consisting of 1307 experimental datapoints gathered from the literature, was ensured through the application of a Monte Carlo outlier detection algorithm, which validated its suitability for model training and validation. …”
Get full text

A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…This study presents a YOLOv8-based binocular vision model for real-time recognition of blasting fragmentation. The model is trained on a dataset comprising 1536 samples, which were annotated using an automatic labeling algorithm and expanded to 7680 samples through data augmentation techniques. …”
Get full text