Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models by Wei Ming, Yukun Bao, Zhongyi Hu, Tao Xiong

“…The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. …”
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Incorporating Severe Maternal Morbidity Into Clinical Prediction Models for Postpartum Cardiovascular Disease by M. Alcantara, G.D. Shapiro, R.W. Platt, M. Abrahamowicz, J.G. Ray, U.V. Ukah, N. Dayan

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Comparison of various machine learning regression models based on Human age prediction by Dr.Manaf K Hussein

Subjects: “…Machine learning, regression model, GPR, Elastic Net, L-SVR, RBF-LVR, RVR, brain-age prediction…”
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Prognostic factors and prediction models for acute aortic dissection: a systematic review by Ling Li, Xin Sun, Jing Tan, Qianrui Li, Kang Zou, Shiyao Huang, Yan Ren, Chunrong Liu

“…Most prediction models were considered at high risk of bias. …”
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Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.) by Isabella Chiaravallotti, Owen Pauptit, Valerio Hoyos‐Villegas

“…For models with low prediction accuracy, the ensemble approach can increase accuracy. …”
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Evaluation of Total Electron Content Prediction Using Three Ionosphere‐Thermosphere Models by O. Verkhoglyadova, X. Meng, A. J. Mannucci, J.‐S. Shim, R. McGranaghan

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Models Development for Prediction of Blast Efficiency and Total Charge in a Typical Quarry by Kayode Augustine Idowu, Zakari Adamu

“… The prediction of blast efficiency is usually achieved by using models; this in turn, gives better and more efficient rock fragmentation. …”
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Validation of sleep-based actigraphy machine learning models for prediction of preterm birth by Benjamin C. Warner, Peinan Zhao, Erik D. Herzog, Antonina I. Frolova, Sarah K. England, Chenyang Lu

“…We evaluate motion actigraphy data collected from a cohort of participants undergoing pregnancy, and train several machine learning models based on aggregate features engineered from this data. …”
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iPRISM: Intelligent Predicting Response to Cancer Immunotherapy through Systematic Modeling by Yinchun Su, Siyuan Li, Qian Wang, Bingyue Pan, Jiyin Lai, Guangyou Wang, Junwei Han, Qingfei Kong

“…Immunotherapy has revolutionized cancer treatment, but predicting patient response remains challenging. Herein, we present iPRISM (Intelligent Predicting Response to cancer Immunotherapy through Systematic Modeling), which is a novel network‐based model that integrates multiomics data to predict immunotherapy outcomes. …”
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Hybrid Machine Learning Model for Predicting the Fatigue Life of Plain Concrete Under Cyclic Compression by Lucas Rodrigues Lunardi, Paulo Guilherme Cornélio, Lisiane Pereira Prado, Caio Gorla Nogueira, Emerson Felipe Felix

“…This study introduces a hybrid machine learning model based on the stacking ensemble strategy, integrating Support Vector Regression (SVR), Random Forest (RF), and Artificial Neural Networks (ANNs) to enhance prediction accuracy. …”
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A Mode Selected Mixed Logic Dynamic Model and Model Predictive Control of Buck Converter by Lei Jiang, Enliang Liu, Ding Liu

“…In establishing the hybrid system model, the factors such as the inductor current are neglected, and the Model Predictive Control (MPC) is used to switch the most favorable working state of the control target. …”
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Research on time factor prediction in the Lee-Carter model—the combined model based on Lp-norm by Xueru Yang, Yue Hu, Wei Zhang, Kuan Xu

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Numerical Predictions of Cavitating Flow around Model Scale Propellers by CFD and Advanced Model Calibration by Mitja Morgut, Enrico Nobile

“…The numerical predictions of the cavitating flow around two model scale propellers in uniform inflow are presented and discussed. …”
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Robust Model-Free Predictive Torque Control for Induction Motor Drive Based on an Ultralocal Model by Md. Belal Hossen, Md. Habibullah

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Application of State Models in a Binary–Temporal Representation for the Prediction and Modelling of Crude Oil Prices by Michał Dominik Stasiak, Żaneta Staszak, Joanna Siwek, Dawid Wojcieszak

“…The presented research confirms the high effectiveness of our state modelling system in predicting oil prices on a level that allows for the construction of financially effective investment decision support systems. …”
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Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept by Saman Dabbaghfeizi, Ali Naderan, Ali Tavakoli-Kashani

Subjects: “…Aggregate crash prediction model (ACPM)…”
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Integrated modeling of SPARC H-mode scenarios: exploration of the impact of modeling assumptions on predicted performance by M. Muraca, P. Rodriguez-Fernandez, N.T. Howard, J. Hall, E. Fable, G. Tardini

“…The simulations have been performed within the ASTRA framework, using the quasi-linear model TGLF SAT2, including electromagnetic effects, for the core transport, and a neural network trained on EPED simulations to predict the pedestal height and width self-consistently. …”
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A Model Predictive Control Strategy with Minimum Model Error Kalman Filter Observer for HMEV-AS by Ying Zhou, Chenlai Liu, Zhongxing Li, Yi Yu

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Predicting lung nodules malignancy by M. Jacob, J. Romano, D. Araújo, J.M. Pereira, I. Ramos, V. Hespanhol

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Comprehensive propagation of errors for the prediction of woody biomass by Stephen H. Roxburgh, Keryn I. Paul

“…Abstract Managing vegetation to sequester carbon in biomass requires estimates to meet standards for accuracy, with methods that are transparent, verifiable and cost‐effective. Allometric models are commonly used to predict biomass from non‐destructive field inventory data. …”
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