Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow by Álvaro Ospina, Ever Herrera Ríos, Jaime Jaramillo, Camilo A. Franco, Esteban A. Taborda, Farid B. Cortes

“…Ultimately, this study supports the sustainability and economic viability of hydroelectric power generation by advancing tools for predictive maintenance and performance optimization.…”
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Deep learning for property prediction of natural fiber polymer composites by Ivan P. Malashin, Dmitry Martysyuk, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov, Vadim Tynchenko

“…Using 180 experimental samples, augmented up to 1500 using bootstrap technique, several regression models–linear, random forest, gradient boosting, DNNs–were developed to predict mechanical behavior. Best DNN model architecture (four hidden layers (128–64–32–16 neurons), ReLU activation, 20% dropout, a batch size of 64, and the AdamW optimizer with a learning rate of $$10^{-3}$$ ) obtained through hyperparameter optimization using Optuna, delivered the best performance (R $$^2$$ up to 0.89) and MAE reductions of 9–12% compared to gradient boosting, driven by the DNN’s ability to capture nonlinear synergies between fiber-matrix interactions, surface treatments, and processing parameters while aligning architectural complexity with multiscale material behavior.…”
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PREDICTION OF LOAD LIMIT OF BI-MODULUS COMPOSITES LAMINATED STRUCTURE by HUANG ZheFeng, LI Li, YANG ZengQin, SHANG FuLin, HOU DeMen

“…Finally,this method is used to examine the load limit of a BFRP arm structure which is a part of space station and obtain the prediction results.…”
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Assessment of methods for predicting physical and chemical properties of organic compounds by Tunga Salthammer

“…For the ecotoxicological assessment of a chemical substance it is important to know its partition behavior. In inanimate nature these are water, soil and air. …”
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Prediction of Vapor-Liquid Equilibria Using CEOS /GE Models

“…The present study investigates the use of different GE mixing rules in cubic equations of state for prediction of phase behavior of multicomponent hydrocarbon systems. …”
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Machine Learning-Based Highway Pavement Performance Prediction in Xinjiang by Qi Yang, Wei Tian, Xiaomin Dai

“…This study introduces a machine-learning-based framework to predict asphalt pavement performance in Xinjiang. …”
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PREDICTION AND DAMAGE ANALYSIS OF THE POSTBUCKLING FOR MULTI-SPAR COMPOSITE BOX by YUAN Fei, CHAI YaNan, ZHANG AYing

“…Aiming at the buckling and postbuckling problems,buckling behavior and damage process of multi-spar composite box under bending-shearing load is researched in this paper. …”
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Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model by Huan Xu

“…To the best of our knowledge, few research studies have been developed to predict students’ performance based on student behavior, and the novelty of this study is to develop a new hybrid intelligent approach in this field. …”
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Machine learning approach to student performance prediction of online learning. by Jing Wang, Yun Yu

“…The critical thought is that eleven learning behavioral indicators are constructed according to online learning process, following that, through analyzing the correlation between the eleven learning behavioral indicators and the scores obtained by students online learning, we filter out those learning behavioral indicators that are weakly correlated with student scores, meanwhile, retain these learning behavior indicators being strongly correlated with student scores, which are used as the eigenvalue indicators. …”
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Springback Prediction of Sandwich Panel Using Machine Learning Methods by Raja Ouled Ahmed Ben Ali, Sami Chatti

“…The purpose of this paper is to obtain a model that quickly predicts springback in the three-point bending process of steel / PUR / steel sandwich panels. …”
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Data-driven organic solubility prediction at the limit of aleatoric uncertainty by Lucas Attia, Jackson W. Burns, Patrick S. Doyle, William H. Green

“…Abstract Small molecule solubility is a critically important property which affects the efficiency, environmental impact, and phase behavior of synthetic processes. Experimental determination of solubility is a time- and resource-intensive process and existing methods for in silico estimation of solubility are limited by their generality, speed, and accuracy. …”
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Can internet search data predict human migration intentions? by Haodong Qi, Holly E. Reed, Pieter Bevelander

“…However, unlike official migration statistics, search data may only reflect the behavior of a self-selected subset of the population, raising concerns about its generalizability. …”
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A New Prediction Model of Dam Deformation and Successful Application by Shuangping Li, Bin Zhang, Meng Yang, Senlin Li, Zuqiang Liu

“…A high-precision prediction model considering spatial correlation is constructed. …”
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Computational prediction of protein interactions in single cells by proximity sequencing. by Junjie Xia, Hoang Van Phan, Luke Vistain, Mengjie Chen, Aly A Khan, Savaş Tay

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Machine learning modeling for predicting adherence to physical activity guideline by Ju-Pil Choe, Seungbak Lee, Minsoo Kang

“…Based on the PFI, sedentary behavior, age, gender, and educational status were the most important variables. …”
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Relative importance of temporal and location features in predicting smoking events by Han Yang, Hang Yu, Michael Kotlyar, Sheena R. Dufresne, Serguei V. S. Pakhomov

“…Mobile technology can help by predicting these events and delivering timely reminders. …”
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A Prediction of Solar Cycle Maxima Using Visibility Graphs by Eduardo Flández, Víctor Muñoz

“…We apply a complex network approach to analyze the time series of five solar parameters, and propose a strategy to predict the number of sunspots for the next solar maximum, and when this maximum will occur. …”
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Prediction of Reservoir Bank Collapse Based on the Limit Equilibrium Theory by Xuetong Ma, Qipeng Li, Hao Zhang, Debin Gao, Jiao Long, Zhengzheng Li

“…With an increase in the bank slope angle, the bank collapse width fluctuates and rises. The prediction model of bank collapse width based on the limit equilibrium theory can better explain the time-dependent behavior of bank collapse. …”
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Optimizing Learning: Predicting Research Competency via Statistical Proficiency by Tarid Wongvorachan, Siwachoat Srisuttiyakorn, Kanit Sriklaub

“…Predictors relating to students’ learning behavior in a statistics course such as assignment completion and academic dishonesty are also included as auxiliary variables. …”
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Nonparametric Comparative Analysis of Driver Behaviors in Signalized and Non-Signalized Roundabouts: A Study on Road Safety in Qatar by Mohammed Abul Fahed, Pilsung Choe, Al-Harith Umlai

“…These findings suggest that traffic signals contribute to safer and more predictable driver behavior, although congestion and long waiting times in signalized roundabouts present challenges. …”
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