Research on telecom industry customer churn prediction based on explainable machine learning models by WANG Shengjie, ZHANG Qinghong

“…Using the actual business data of a communication company in Xinjiang, the prediction model was constructed through data preprocessing and feature engineering, and five major key performance indicators were selected to evaluate the model performance. …”
Get full text

Multi-Scenario Remote Sensing Image Forgery Detection Based on Transformer and Model Fusion by Jinmiao Zhao, Zelin Shi, Chuang Yu, Yunpeng Liu

“…First, we explore the performance of various excellent feature extraction networks in this task under the constructed unified classification framework. …”
Get full text

Comparative study of state-based neural networks for virtual analog audio effects modeling by Riccardo Simionato, Stefano Fasciani

“…We evaluate the performance and limitations of these models using multiple metrics, providing insights for future research and development. …”
Get full text

Ground data analysis for PM2.5 Prediction using predictive modeling techniques by Elham Nourmohammad, Yousef Rashidi

“…The models were evaluated based on performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R² scores. …”
Get full text

Modelling district heating demand: A synthetic dataset for two residential neighbourhoodsZenodo by Katia Ritosa, Ina De Jaeger, Dirk Saelens, Staf Roels

“…The datasets feature only heavy-weight houses in terraced, semi-detached or detached configurations, modelled as either single- or two-zone buildings, depending on their number of storeys. …”
Get full text

DINOV2-FCS: a model for fruit leaf disease classification and severity prediction by Chunhui Bai, Chunhui Bai, Chunhui Bai, Lilian Zhang, Lilian Zhang, Lilian Zhang, Lutao Gao, Lutao Gao, Lutao Gao, Lin Peng, Lin Peng, Lin Peng, Peishan Li, Peishan Li, Peishan Li, Linnan Yang, Linnan Yang, Linnan Yang

“…The mIoU of the trained model reached 83.95%, and the accuracy of disease severity grading was 95.24%.DiscussionThe results demonstrate that the model exhibits superior performance compared to other state-of-the-art models and that the model has strong generalization capabilities. …”
Get full text

Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…A stratified sampling strategy was used to ensure balanced class distribution, and model performance was further validated using k-fold cross-validation to enhance robustness and generalizability. …”
Get full text

Automated Arrhythmia Classification System: Proof-of-Concept With Lightweight Model on an Ultra-Edge Device by Namho Kim, Seongjae Lee, Seungmin Kim, Sung-Min Park

“…The lightweight model was integrated into a wearable sensing device featuring a resource-constrained microcontroller unit. …”
Get full text

A Hybrid Framework for Referring Image Segmentation: Dual-Decoder Model with SAM Complementation by Haoyuan Chen, Sihang Zhou, Kuan Li, Jianping Yin, Jian Huang

“…Furthermore, while the PolyFormer model has shown impressive performance in RIS, its large number of parameters and high training data requirements pose significant challenges. …”
Get full text

ParaAntiProt provides paratope prediction using antibody and protein language models by Mahmood Kalemati, Alireza Noroozi, Aref Shahbakhsh, Somayyeh Koohi

“…Various conducted ablation studies, which elaborate on the impact of each part of the model on the prediction task, show that the improvement in prediction performance by applying CDR positional encoding together with CNNs depends on the specific protein and antibody language models used. …”
Get full text

Modelling of QUENCH-03 and QUENCH-06 Experiments Using RELAP/SCDAPSIM and ASTEC Codes by Tadas Kaliatka, Algirdas Kaliatka, Virginijus Vileiniškis, Eugenijus Ušpuras

“…The performed benchmark allowed analysing different modelling features. …”
Get full text

A Comparative Study of Drug Prediction Models using KNN, SVM, and Random Forest by Susi Eva Maria Purba

“…The dataset, obtained from Kaggle, was preprocessed and split into training and testing sets to evaluate model performance using accuracy as the primary metric. …”
Get full text

MDCFVit-YOLO: A model for nighttime infrared small target vehicle and pedestrian detection. by Huiying Zhang, Qinghua Zhang, Yifei Gong, Feifan Yao, Pan Xiao

“…The backbone network uses the lightweight Repvit model, improving detection performance and reducing model weight through transfer learning. …”
Get full text

Constructing a prediction model for acute pancreatitis severity based on liquid neural network by Jie Cao, Shike Long, Huan Liu, Fu’an Chen, Shiwei Liang, Haicheng Fang, Ying Liu

“…Data imbalance was dealt with by data preprocessing and using the synthetic minority oversampling technique (SMOTE). A new feature selection method was designed to optimize model performance. …”
Get full text

Abstract 191: Simulating Intracranial Stenosis: A Methodological Approach In An In‐Vitro Neurovascular Model by Riccardo Daniel Tiberi, Jiahui Li, Joan Vargas, Magda Jablonska, Judith Cendrero, Pere Canals, Marc Molina, Alejandro Tomasello, Marc Ribo

“…Conclusion The developed ICAD model is anatomically accurate and offers realistic physiological and procedural features. …”
Get full text

Acausal Fuel Cell Simulation Model for System Integration Analysis in Early Design Phases by Leonardo Cavini, Susan Liscouët-Hanke, Nicole Viola

“…The model performance is validated through a comparison of the simulated polarization curves with real datasheet data. …”
Get full text

Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models by David Crampen, Joerg Blankenbach

“…Additionally, the proposed modular workflow can be easily customized to fit diverse data sources and enhance semantic segmentation performance in a model-agnostic way.…”
Get full text

Enhanced Models for Wind, Solar Power Generation, and Battery Energy Storage Systems Considering Power Electronic Converter Precise Efficiency Behavior by Binxin Zhu, Junliang Liu, Shusheng Wang, Zhe Li

“…This paper introduces an accurate efficiency model applicable to different types of PECs, and establishes an enhanced mathematical model along with constraint conditions for WT–PV–BES–grid–load systems, based on precise converter efficiency models. …”
Get full text

Research on Ship Engine Fuel Consumption Prediction Algorithm Based on Adaptive Optimization Generative Network by Defu Zhang, Yuxuan Song, Jianfeng Gao, Zhenyu Shen, Liangkuan Li, Anren Yao

“…This approach leverages the strengths of diffusion models in nonlinear generative modeling, integrates meta-learning mechanisms to enhance task adaptation speed, employs multi-head attention modules to strengthen feature extraction, and incorporates dynamic residual connections to improve training stability and flexibility. …”
Get full text

Damage and failure modeling of lotus-type porous material subjected to low-cycle fatigue by J. Kramberger, K. Sterkuš, S. Glodež

“…This paper evaluates a numerical approach for determining of damage initiation and evolution of lotus-type porous material with computational simulations, where the considered computational models have different pore topology patterns. The low-cycle fatigue analysis was performed by using a damage evolution law. …”
Get full text