A Team-Compatibility Decision Support System for the National Football League by Young W.A., Weckman G.R.

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Soil moisture forecasting from sensors-based soil moisture, weather and irrigation observations: A systematic review by Iustina Ivanova

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Methods of a Priori Statistical Analysis of Disturbed Motion of Aircraft in Turbulent Environments by Alexander S. Ermilov, Olga A. Saltykova

“…The article discusses the methods of a priori statistical analysis used for predicting perturbed motion of aircraft in turbulent environments. …”
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Evaluating Bias Correction Methods Using Annual Maximum Series Rainfall Data from Observed and Remotely Sensed Sources in Gauged and Ungauged Catchments in Uganda by Martin Okirya, JA Du Plessis

“…Four bias correction methods, Quantile Mapping (QM), Linear Transformation (LT), Delta Multiplicative (DM), and Polynomial Regression (PR), were evaluated using daily rainfall data from four gauged stations (Gulu, Soroti, Jinja, Mbarara). …”
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Combining Environmental Variables and Machine Learning Methods to Determine the Most Significant Factors Influencing Honey Production by Johanna Ramirez-Diaz, Arianna Manunza, Tiago Almeida de Oliveira, Tania Bobbo, Francesco Nutini, Mirco Boschetti, Maria Grazia De Iorio, Giulio Pagnacco, Michele Polli, Alessandra Stella, Giulietta Minozzi

“…This study aimed to identify the most important features and predict Total Honey Harvest (THH) by combining machine learning (ML) methods with climatic conditions and environmental factors recorded from the winter before and during the harvest season. …”
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Micromechanical modeling and evaluation of CNTs reinforced magnesium matrix composites based on stress softening modified constitutive model by Mingjie Shen, Baojian Han, Tao Ying, Jingya Wang, Liping Zhou, Xiangzhen Xue, Yang Gao, Zongyang Yang

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Comprehensive evaluation of U-Net based transcranial magnetic stimulation electric field estimations by Taylor A Berger, Kathleen Mantell, Zachary Haigh, Nipun Perera, Ivan Alekseichuk, Alexander Opitz

“…Our findings indicate that while deep learning has the potential to significantly accelerate electric field predictions, the precision it achieves needs to be evaluated for the specific TMS application.…”
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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…The method integrates MD simulations for atomic-level interactions using Lennard-Jones and embedded-atom method (EAM) potentials, FEM-based continuum mechanics for stress-strain analysis and thermal response evaluation, and ML techniques trained on multiscale descriptors (e.g., bond energy, stress tensor, coordination number) to model nonlinear property relations and accelerate design iteration. …”
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Construction and evaluation of a triage assessment model for patients with acute non-traumatic chest pain: mixed retrospective and prospective observational study by Xuan Zhou, Gangren Jian, Yuefang He, Yating Huang, Jie Zhang, Shengfang Wang, Yunxian Wang, Ruofei Zheng

“…A nomogram was built based on the predictors, and an internal evaluation was performed using bootstrap resampling methods. …”
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Experimental and Numerical Study to Enhance Granule Control and Quality Predictions in Pharmaceutical Granulations by Maroua Rouabah, Inès Esma Achouri, Sandrine Bourgeois, Stéphanie Briançon, Claudia Cogné

“…A systematic model employing the discrete element method (DEM) was developed herein to gain insights into and better control this process. …”
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Development of a Numerical Prediction Method for the Strain Energy Density of Welded Joints Using Structural Stresses Derived from Nodal Forces by Simone Lucertini, Giulia Morettini, Filippo Cianetti

“…The analysis considers plates of different thicknesses and weld sizes. The proposed method combines the two mentioned approaches to exploit the advantages of both, allowing a fast preliminary investigation of numerous and complex welded joints within a simplified model, with a coarse mesh and no geometric pre-processing required, while keeping a good adherence to the precision benefits given by local energy evaluations. …”
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Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

“…Methods To optimize the performance of classical machine learning on customer churn prediction tasks, this study introduces an extension framework called CostLearnGAN, a tabular generative adversarial network (GAN)-hybrid sampling method, and cost-sensitive Learning. …”
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Predicting Protein Interactions Using a Deep Learning Method-Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine by Yanbin Wang, Zhuhong You, Liping Li, Li Cheng, Xi Zhou, Libo Zhang, Xiao Li, Tonghai Jiang

“…To further evaluate the performance of our method, we compare it with the support vector machine- (SVM-) based method. …”
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Detection of FAM172A expressed in circulating tumor cells is a feasible method to predict high-risk subgroups of colorectal cancer by Chun-Hui Cui, Ri-hong Chen, Duan-Yang Zhai, Lang Xie, Jia Qi, Jin-Long Yu

“…Mesenchymal circulating tumor cells and FAM172A detection may predict highrisk stage II colorectal cancer. Our research proved that circulating tumor cells were feasible surrogate samples to detect gene expression and could serve as a predictive biomarker for tumor evaluation.…”
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Nonlinear mixed‐effects modeling as a method for causal inference to predict exposures under desired within‐subject dose titration schemes by Christian Bartels, Martina Scauda, Neva Coello, Thomas Dumortier, Björn Bornkamp, Giusi Moffa

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Machine Learning-Based Backpressure Unstart Prediction and Warning Method for Combined Cycle Engine Hypersonic Inlet-Oriented Wide Speed Range by Ke Min, Tanbao Hong, Zejun Cai, Lianchen Yu, Chengxiang Zhu, Jianping Zeng

“…Finally, the proposed method and prediction models are validated by wind tunnel experimental data.…”
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Cranial ultrasound as a complementary method to the general movements assessment in preterm infants for predicting the neurological outcome - a single center experience by Zlatanović Dragan, Čolović Hristina, Živković Vesna, Stanković Anita, Kostić Milica, Pejčić Vuk, Radovanović Vukota

“…Preterm birth is considered a risk factor for abnormal neurological development. The study aimed to evaluate the significance of CUS in preterm infants as a complementary method to the General Movements Assessment for predicting neurological outcomes. …”
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A data-driven prediction method for shear bearing capacity of flexural-shear type RC column based on PCC-XGB-SHAP by Tao Huang, Chunfeng Wan, Tingbin Liu, Changqing Miao

“…Results indicate that the XGB model has the highest accuracy and robust generalization ability, making it the most suitable ML method for shear capacity prediction. Based on the prediction data of the optimized model, the SHAP method is applied to address the model interpretability issue in the shear bearing capacity prediction of flexure-shear RC columns. …”
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Egg freshness during storage: the effect of laying hen age and shelf life prediction using a novel hybrid modeling method by Yifeng Lu, Jing Li, Zihao He, Linyun Chen, Huixin Tian, Chen Xu, Xinglian Xu, Minyi Han

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A Novel Rubber Composite Sleeper-Deformation-Prediction Model Based on Response Surface Method (RSM) and Machine Learning (ML) Techniques by Abdulmumin Ahmed Shuaibu, Zhiping Zeng, Ibrahim Hayatu Hassan, Wang Weidong, Hassan Suleiman Otuoze, Suleiman Abdulhakeem, Bushrah Baba Abdulrahman

“…To ensure accurate ML predictions, the dataset was split into 70% for training and 30% for testing. …”
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