Data-driven EV charging infrastructure with uncertainty based on a spatial–temporal flow-driven (STFD) models considering batteries by Talal Alharbi, Ahmed Abdalrahman, Mostafa H. Mostafa

“…The ESS placement is modeled as a multi-objective optimization problem, aiming to enhance voltage stability, reduce power losses, and improve voltage profiles. …”
Get full text

Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models by Weihong Ma, Xingmeng Wang, Simon X. Yang, Lepeng Song, Qifeng Li

“…Overall, the TIRPigEar dataset demonstrates optimal performance when applied to the YOLOv9m algorithm. …”
Get full text

Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning by Hui Xu, Xingwang Peng, Ziyu Peng, Rui Wang, Rui Zhou, Lianguo Fu

“…First, dual feature selection was conducted to identify important feature variables for model construction. Second, ML models were constructed based on the logistic regression (LR), decision tree (DT), support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms, after which random sampling and tenfold cross-validation were separately used to evaluate and compare these models and identify the optimal model. …”
Get full text

Prediction of three-year all-cause mortality in patients with heart failure and atrial fibrillation using the CatBoost model by Jiacan Wu, Guanghong Tao, Siyuan Xie, Han Yang, Fenglin Qi, Naiyue Bao, Zhuo Li, Guanglei Chang, Hua Xiao

“…Conclusions CatBoost was identified as the optimal model for predicting three-year all-cause mortality in HF-AF patients, potentially aiding clinicians in risk stratification and individualized treatment planning to improve patient outcomes.…”
Get full text

Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation by Vivash Naidoo, Ikechukwu Achilonu, Sheefa Mirza, Rodney Hull, Jeyalakshmi Kandhavelu, Marushka Soobben, Clement Penny

“…Following this, molecular dynamics modelling revealed that Tunicamycin C binding induced a conformational perturbation in the 3D structures of TK1 and PKAc, inhibiting their activities. …”
Get full text

Ensemble Machine Learning Model Prediction and Metaheuristic Optimisation of Oil Spills Using Organic Absorbents: Supporting Sustainable Maritime by Le Quang Dung, Pham Duc, Bui Thi Anh Em, Nguyen Lan Huong, Nguyen Phuoc Quy Phong, Dang Thanh Nam

“…To close this gap, our work combines metaheuristic algorithms with ensemble machine learning and suggests a hybrid technique for the precise prediction and improvement of oil removal efficiency. …”
Get full text

Power Control and Voltage Regulation for Grid-Forming Inverters in Distribution Networks by Xichao Zhou, Zhenlan Dou, Chunyan Zhang, Guangyu Song, Xinghua Liu

“…An enhanced whale optimization algorithm (EWOA) is designed to complete the algorithm solution, thereby achieving the optimal system configuration, where an improved attenuation factor and position updating mechanism is proposed to enhance the EWOA’s global optimization capability. …”
Get full text

A Two-Sided Stable Matching Model of Cloud Manufacturing Tasks and Services considering the Nonlinear Relationship between Satisfaction and Expectations by Yujie Zheng, Meiyan Li, Jiakun Liu

“…Finally, an adaptive genetic algorithm (AGA) is designed to solve the proposed two-sided matching model. …”
Get full text

Automating the Design of Scalable and Efficient IoT Architectures Using Generative Adversarial Networks and Model-Based Engineering for Industry 4.0 by William Villegas-Ch, Jaime Govea, Diego Buenano-Fernandez, Aracely Mera-Navarrete

“…Traditional approaches, such as heuristic and genetic algorithms, have proven insufficient in automating and optimizing large-scale IoT configurations, resulting in a high design and validation time cost. …”
Get full text

SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Subsequently, the refined data undergoes feature selection employing an improved pigeon-inspired optimizer (PIO) algorithm. …”
Get full text

Urban Land-use Features Mapping from LiDAR and Remote Sensing Images using Visual Transformer Network Model by Q. Yuan

“…Finally, it is found that the proposed algorithm is generally better than other representative methods, and the classification accuracy using remote sensing data and LiDAR is improved. …”
Get full text

Memory-Efficient Batching for Time Series Transformer Training: A Systematic Evaluation by Phanwadee Sinthong, Nam Nguyen, Vijay Ekambaram, Arindam Jati, Jayant Kalagnanam, Peeravit Koad

Get full text

Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…All models employed the random forest algorithm and were trained on daily-scale ET observations, in-situ meteorological data and satellite remote sensing. …”
Get full text

HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…Furthermore, the overall generalization ability of the model is improved through hyperparameter optimization based on the tree-structured Parzen estimator (TPE). …”
Get full text

Let’s get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony by Thijs P. Rietveld, Björn J. P. van der Ster, Abraham Schoe, Henrik Endeman, Anton Balakirev, Daria Kozlova, Diederik A. M. P. J. Gommers, Annemijn H. Jonkman

“…To move from bench to bedside implementation, data quality should be improved and algorithms that can detect multiple PVAs should be externally validated, incorporating measures for breathing effort as ground truth. …”
Get full text

Enhancing Performance and Stability of Wing-Alone UAV: A Comprehensive Mathematical Model and Simulation Approach Using MATLAB and Simulink by G. Ramanan, N. Rahul, V. E. Sathishkumar, Indraraj Upadhyaya

“…The novel objective of this study is enhancing the performance and stability aspects of the wing-alone UAV through code-based reports and the implementation of custom MATLAB algorithms. The wing-alone UAV demonstrated a 15% improvement in aerodynamic efficiency and a 10% reduction in overall weight compared to baseline designs. …”
Get full text

Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…Key influencing factors (e.g., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. …”
Get full text

Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model by Md. Siddikur Rahman, Miftahuzzannat Amrin, Md. Abu Bokkor Shiddik

“…The optimal tree‐based ML model with strong interpretability was created by comparing various ML models using the hyperparameter optimization technique. …”
Get full text

Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
Get full text

Deep Reinforcement Learning Based Active Disturbance Rejection Control for ROV Position and Attitude Control by Gaosheng Luo, Dong Zhang, Wei Feng, Zhe Jiang, Xingchen Liu

“…The deep deterministic policy gradient (DDPG) algorithm was used to optimize the linear extended state observer (LESO). …”
Get full text