The data-driven localized wave solutions of KdV-type equations via physics-informed neural networks with a priori information by Zhi-Ying Feng, Xiang-Hua Meng, Xiao-Ge Xu

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A Pressure-Driven Recovery Factor Equation for Enhanced Oil Recovery Estimation in Depleted Reservoirs: A Practical Data-Driven Approach by Tarek Al Arabi Omar Ganat

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Data-driven model reconstruction for nonlinear wave dynamics by Ekaterina Smolina, Lev Smirnov, Daniel Leykam, Franco Nori, Daria Smirnova

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Kinetic data-driven approach to turbulence subgrid modeling by G. Ortali, A. Gabbana, N. Demo, G. Rozza, F. Toschi

“…This foundational study lays the basis for extending the proposed framework to different turbulent flow settings and—most importantly—to develop new classes of hybrid data-driven kinetic-based models capable of faithfully capturing the complex macroscopic dynamics of diverse physical systems such as emulsions, non-Newtonian fluid, and multiphase systems.…”
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Data-driven model discovery and model selection for noisy biological systems. by Xiaojun Wu, MeiLu McDermott, Adam L MacLean

“…Biological systems exhibit complex dynamics that differential equations can often adeptly represent. Ordinary differential equation models are widespread; until recently their construction has required extensive prior knowledge of the system. …”
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A Stable Implementation of a Data‐Driven Scale‐Aware Mesoscale Parameterization by Pavel Perezhogin, Cheng Zhang, Alistair Adcroft, Carlos Fernandez‐Granda, Laure Zanna

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Scalability analysis of heavy-duty gas turbines using data-driven machine learning by Shubhasmita Pati, Julian D. Osorio, Mayank Panwar, Rob Hovsapian

“…The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. …”
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A theory and data-driven method for rapid bottom hole pressure calculation in UGS by Yang Li, Haiwei Guo, Xianfeng Gong, Naixin Lu, Kairui Zhang

“…Finally, by integrating the wellbore flow equations under different well conditions, using theoretical models to generate samples, and establishing a loss function guided by real samples, a theory and data-driven neural network model (TDDNN) has been successfully developed, achieving rapid and accurate calculation of bottom hole pressure. …”
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Impact of Feature-Selection in a Data-Driven Method for Flow Curve Identification of Sheet Metal by Quang Ninh Hoang, Hyungbum Park, Dang Giang Lai, Sy-Ngoc Nguyen, Quoc Tuan Pham, Van Duy Dinh

“…This study presents an innovative data-driven methodology to model the hardening behavior of sheet metals across a broad strain range, crucial for understanding sheet metal mechanics. …”
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Data-driven modeling of the Yld2000 yield criterion and its efficient application in numerical simulation by Xiaomin Zhang, Jianzhong Mao, Zhi Cheng

“…The trained models are subsequently integrated into the ABAQUS user material subroutine (UMAT) to enable data-driven yield criterion simulations. This approach not only circumvents the cumbersome partial differential equation solutions inherent in traditional analytical methods but also overcomes the challenges associated with Physics-Informed Neural Networks (PINN), such as boundary condition determination and computational stability. …”
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Data-driven soil salinization mapping: risk prediction and uncertainty quantification based on Bayesian inference by Yujian Yang, Ying Zhao, Rongjiang Yao, Xueqin Tong

“…KDE of 100 groups of predicted values showed a good fit based on data-driven soil EC, higher levels of uncertainty associated with soil EC correspond to areas where the gaussian distributions overlap using Theano, as PyMC3 core component based on deep learning principles.…”
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A data driven approach using local measurements to locate turbine governors causing forced oscillations by Sigurd Hofsmo Jakobsen, Xavier Bombois, Santiago Sanchez Acevedo, Hallvar Haugdal, Salvatore D’Arco

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Daily reference evapotranspiration prediction using empirical and data-driven approaches: A case study of Adana plain by Semin Topaloğlu Paksoy, Deniz Levent Koç

“…The objective of this research was to examine the effectiveness of five different data-driven techniques, including artificial neural networks "multilayer perceptron" (ANN), gene expression programming (GEP), random forest (RF), support vector machine "radial basis function" (SVM), and multiple linear regression (MLR) to model the daily ET0. …”
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Advancements in understanding emission characteristics, data-driven olfactory-chemical measurements, and health impacts of the emerging odor pollution by Xinyuan Xu, Haixin Gu, Zihao Zhang, Yantong Liu, Lingling Zhang, Junfeng Wang, Mindong Chen, Yu Huang, Junji Cao, Shun-cheng Lee, Haiwei Li, Xinlei Ge

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Extending the TPB of residential waste sorting with situational factors using a data-driven approach: The case of Gothenburg, Sweden by Jonathan Cohen, Jorge Gil, Leonardo Rosado

“…The Theory of Planned Behaviour (TPB) has been extensively applied to determining the importance of different psychological constructs in waste sorting behaviour. …”
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Data driven frequency ratio modeling for iron-ore exploration using aster and aeromagnetic datasets in parts of Nasarawa, Northcentral Nigeria by Ayokunle Adewale Akinlalu, Oluwarotimi Samuel Olowe, Daniel Oluwafunmilade Afolabi, Olabanji Odunayo Aladejana

“…The frequency ratio model (FR) was used to assign weights to different layers of evidence and develop a conceptual model of mineralization potential. …”
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RESEARCH ON EXCAVATION RESISTANCE OF ADAMS-EDEM COUPLING SIMULATION DRIVEN BY MEASURED DATA AND THEORETICAL MODEL (MT) by WU Di, WANG ShenLong, LI GuanYun, DING XiaoHong, YU HuiJie, NI WeiYu

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Evaluation of deceased-donor kidney offers: development and validation of novel data driven and expert based prediction models for early transplant outcomes by Christoph F. Mahler, Felix Friedl, Christian Nusshag, Claudius Speer, Louise Benning, Daniel Göth, Matthias Schaier, Claudia Sommerer, Markus Mieth, Arianeb Mehrabi, Christoph Michalski, Lutz Renders, Quirin Bachmann, Uwe Heemann, Markus Krautter, Vedat Schwenger, Fabian Echterdiek, Fabian Echterdiek, Martin Zeier, Christian Morath, Florian Kälble

“…The expert model is based on predictor ratings by senior transplant nephrologists, while for the data-driven model variables were selected via high-dimensional lasso generalised estimating equations (LassoGee). …”
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Optimising Physics-Informed Neural Network Solvers for Turbulence Modelling: A Study on Solver Constraints Against a Data-Driven Approach by William Fox, Bharath Sharma, Jianhua Chen, Marco Castellani, Daniel M. Espino

“…A standard full equation PINNs model with predicted first-order stress terms was compared against reduced-boundary models and reduced-order models, with different levels of assumptions made about the flow to monitor the effect on the flow field predictions. …”
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Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature by Muhammad Ishtiaq, Saurabh Tiwari, Molakatala Nagamani, Sung-Gyu Kang, Nagireddy Gari Subba Reddy

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