Electrochemical–Thermal Modeling of Lithium-Ion Batteries: An Analysis of Thermal Runaway with Observation on Aging Effects by Milad Tulabi, Roberto Bubbico

“…Additionally, a machine learning algorithm (logistic regression) is employed to identify an internal resistance threshold, beyond which thermal runaway (TR) becomes highly probable, and to predict TR probability based on key battery parameters. …”
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Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens by Danilo Florentino Pereira, Irenilza de Alencar Nääs, Saman Abdanan Mehdizadeh

“…This study supports the integration of Optical Flow and Unrest Index technologies into precision livestock systems, offering a foundation for predictive welfare management at scale.…”
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Potential natural vegetation pattern based on major tree distribution modeling in the western Rif of Morocco by Ghallab A, Boubekraoui H, Laaribya S, Ben-Said M

“…In a fragile ecological environment, understanding the potential spatial distribution of species and the underlying environmental conditions is crucial for resolving ecosystem management issues and predicting impacts of global change. This study aimed to determine the potential distribution of fourteen major Mediterranean taxa (seven conifers and seven broadleaves) native to northwestern Morocco using the Maximum Entropy Algorithm (MaxEnt). …”
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Artificial Intelligence in Medicine: Transforming The Future of Healthcare by Tashfeen Alam Jan, Shumaila Naz

“…Ensuring data privacy, promoting algorithm transparency, and maintaining fairness in AI-driven healthcare solutions are key concerns. …”
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Addressing water scarcity challenges through rainwater harvesting: A comprehensive analysis of potential zones and model performance in arid and semi-arid regions–A case study on P... by Subhra Halder, Suddhasil Bose

“…Approximately 2% of the area is unsuitable, 8% is poorly suitable, 33% is moderately suitable, 45% is highly suitable, and the remaining 12% is extremely suitable in Purulia. Two predictive models were developed, with the RF algorithm demonstrating nearly 99% accuracy. …”
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Mechanisms and optimization for simultaneous removal of Cd(II) and Sb(V) from aqueous solutions using birnessite and fulvic acid composite by Changsheng Jin, Jingjing Lu, Yin Gao, Baowei Hu, Yuxi Liu

“…The RF model demonstrated superior predictive accuracy (R² = 0.8037, RMSE = 0.0625) compared to the RSM and GABP models. …”
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Downscaling of ERA5 reanalysis land surface temperature based on attention mechanism and Google Earth Engine by Shiyu Li, Hong Wan, Qun Yu, Xinyuan Wang

“…In addition, the Bayesian global optimization algorithm is used to select the optimal hyperparameters of the network in order to enhance the predictive performance of the model. …”
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Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…Conclusion The DRG-based prognostic model demonstrated strong predictive power in COAD, highlighting the potential of DRGs as therapeutic targets. …”
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Estimation of Solar Diffuse Radiation in Chongqing Based on Random Forest by Peihan Wan, Yongjian He, Chaoyu Zheng, Jiaxiong Wen, Zhuting Gu

“…A high-precision DIFRA estimation model was developed using the random forest algorithm, and a distributed simulation of DIFRA in Chongqing was achieved. …”
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Comprehensive analysis of cuproptosis-related genes in immune infiltration and development of a novel diagnostic model for acute kidney injury by Yajing Li, Yingxue Ding

“…The six-gene cuproptosis-related signature exhibited remarkable predictive efficiency for AKI.…”
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Human-caused ignition pathways under climate change scenarios in Eastern Spain by Pere Gelabert, Adrián Jiménez-Ruano, Jaime Ribalaygua, Luís Torres, Marcos Rodrigues

“…The model achieved satisfactory predictive performance (AUC = 0.76 ± 0.01). We observed a generalized increase in the probability of ignition in all scenarios linked to climate warming decreasing DFMC, except in SSP1-2.6. …”
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Edge computing-based ensemble learning model for health care decision systems by Asir Chandra Shinoo Robert Vincent, Sudhakar Sengan

“…The main drawback of traditional Machine Learning (ML) techniques is their failure to predict reliably. To solve this problem, the proposed model creates an Ensemble Extreme Learning Machine (EN-ELM) algorithm that combines predictors trained on several different data sets. …”
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Thermal Monitoring of an Internal Combustion Engine for Lightweight Fixed-Wing UAV Integrating PSO-Based Modelling with Condition-Based Extended Kalman Filter by Aleksander Suti, Gianpietro Di Rito, Giuseppe Mattei

“…The monitoring algorithm, being executable in real-time and capable of identifying incipient degradations of the thermal flow, demonstrates applicability for online diagnostics and predictive maintenance purposes.…”
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Principles of creating a digital twin prototype for the process of alkylation of benzene with propylene based on a neural network by K. G. Kichatov, T. R. Prosochkina, I. S. Vorobyova

“…A microcontroller prototype of the process was created.Results. A predictive neural network model and its creation algorithm for the process of benzene alkylation was developed. …”
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Chess Position Evaluation Using Radial Basis Function Neural Networks by Dimitrios Kagkas, Despina Karamichailidou, Alex Alexandridis

“…The models produced with the proposed approach are suitable for integration in model-based decision-making frameworks, e.g., model predictive control (MPC) schemes, which could form the basis for a fully-fledged chess-playing software.…”
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MACHINE LEARNING FOR CONCRETE SUSTAINABILITY IMPROVEMENT: SMART FLEET MANAGEMENT by Coralia TANASUICA (ZOTIC), Mihai Daniel ROMAN

“…Furthermore, the Long Short-Term Memory (LSTM) algorithm is used for forecasting fuel consumption, offering a predictive glance into future expenditures. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. …”
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Confirmation of the reported association of clonal chromosomal mosaicism with an increased risk of incident hematologic cancer. by Ursula M Schick, Andrew McDavid, Paul K Crane, Noah Weston, Kelly Ehrlich, Katherine M Newton, Robert Wallace, Ebony Bookman, Tabitha Harrison, Aaron Aragaki, David R Crosslin, Sophia S Wang, Alex P Reiner, Rebecca D Jackson, Ulrike Peters, Eric B Larson, Gail P Jarvik, Christopher S Carlson

“…Chromosomal abnormalities provide clinical utility in the diagnosis and treatment of hematologic malignancies, and may be predictive of malignant transformation in individuals without apparent clinical presentation of a hematologic cancer. …”
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Integrated OVMD-BiGRU-SMAC Framework for Forecasting Construction Accidents in the Kingdom of Saudi Arabia by Badr T. Alsulami, Afaq Khattak

“…These IMFs are individually forecasted using Bidirectional Gated Recurrent Unit (BiGRU) models, which are capable of learning sequential patterns in both temporal directions. To enhance the predictive accuracy, the hyperparameters of each BiGRU model are optimized using the Sequential Model-based Algorithm Configuration (SMAC) technique. …”
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Adaptive Entry Guidance for Hypersonic Gliding Vehicles Using Analytic Feedback Control by Xunliang Yan, Peichen Wang, Shaokang Xu, Shumei Wang, Hao Jiang

“…Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. …”
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