Root Cause Analysis in Industrial Manufacturing: A Scoping Review of Current Research, Challenges and the Promises of AI-Driven Approaches by Dominik Pietsch, Marvin Matthes, Uwe Wieland, Steffen Ihlenfeldt, Torsten Munkelt

Subjects: “…root cause analysis…”
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Kinetic data-driven approach to turbulence subgrid modeling by G. Ortali, A. Gabbana, N. Demo, G. Rozza, F. Toschi

“…Here, we demonstrate that, by properly tuning, a kinetic approach can statistically reproduce the quantitative dynamics of the larger scales in turbulence, thereby providing an alternative, computationally efficient and physically rooted approach toward subgrid scale (SGS) modeling in turbulence. …”
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Data-driven Static Equivalence with Physics-informed Koopman Operators by Wei Lin, Changhong Zhao, Maosheng Gao, C. Y. Chung

“…To tackle this challenge, this letter proposes a novel data-driven method to improve equivalency accuracy of DNs with distributed energy resources. …”
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Image-data-driven simulation of fluid dynamics (proposal and evaluation) by Nobuto NAKAMICHI, Younghwa CHO, Nobuyuki OSHIMA

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A Data-Driven Multi-Step Flood Inundation Forecast System by Felix Schmid, Jorge Leandro

“…To provide a dynamic inundation map in real-time, we developed a data-driven multi-step inundation forecast system for fluvial flood events. …”
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Harnessing Novel Data‐Driven Techniques for Precise Rainfall–Runoff Modeling by Saad Sh. Sammen, Reza Mohammadpour, Karam AlSafadi, Ali Mokhtar, Shamsuddin Shahid

“…The models' performance can be ranked based on the testing data in the following order: GMDH, ELM, ANN + GA, and ANN + CUKOO. The root mean squared error (RMSE) was recorded as 56.7 and 69.7 m3/s for the GMDH and ELM models, respectively. …”
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Data-Driven Neural Differential Equation Model and Stochastic Dynamics for Glioma Prediction by Mohammed Salman, Sanjay Kumar Mohanty

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Data-Driven Dynamic Optimization for Hosting Capacity Forecasting in Low-Voltage Grids by Md Tariqul Islam, M. J. Hossain, Md Ahasan Habib

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Data driven healthcare insurance system using machine learning and blockchain technologies by Irum Matloob, Shoab Khan, Bushra Bashir, Rukaiya Rukaiya, Javed Ali Khan, Hessa Alfraihi

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Data-driven protease engineering by DNA-recording and epistasis-aware machine learning by Lukas Huber, Tim Kucera, Simon Höllerer, Karsten Borgwardt, Sven Panke, Markus Jeschek

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Estimation of Evaporation Rate Using Advanced Methods by Mohammed Falah Allawi, Uday Hatem Abdulhameed, Mohammed Freeh Sahab, Sadeq Oleiwi Sulaiman

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Hybrid Model–Data-Driven Radar Jamming Effectiveness Evaluation Method for Accuracy Improvement by Runyang Chen, Yi Zhang, Xiuhe Li, Jinhe Ran, Qianqian Shi

“…The current model-driven evaluation method has low confidence and the data-driven evaluation method lacks sufficient high-quality data; thus, the evaluations that are solely model-driven or data-driven are not effective. …”
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Data-Driven Prediction of Binder Rheological Performance in RAP/RAS-Containing Asphalt Mixtures by Eslam Deef-Allah, Magdy Abdelrahman

“…This study suggests a data-driven framework that considers the rheological, chemical, and thermal characteristics to predict the binders’ performance. …”
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Improving Aquaculture Worker Safety: A Data-Driven FTA Approach with Policy Implications by Su-Hyung Kim, Seung-Hyun Lee, Kyung-Jin Ryu, Yoo-Won Lee

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Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils by Shahbaz Ahmad, Siraj Ahmad, Sabih Akhtar, Faraz Ahmad, Mujib Ahmad Ansari

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Research on Data-Driven Performance Assessment and Fault Early Warning of Marine Diesel Engine by Haiyan Wang, Zihan Wang, Biao Shi

“…To enable proactive prediction of marine diesel engine failure time and root causes, thereby reserving sufficient time for maintenance, this study proposes a data-driven multi-algorithm integration framework for performance assessment and fault early warning in marine diesel engines. …”
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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

“…The novel method significantly outperforms traditional techniques across five precision metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and an enhanced R-squared (R2) value. …”
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Estimation of state of health for lithium-ion batteries using advanced data-driven techniques by Smitanjali Rout, Sudhansu Kumar Samal, Demissie Jobir Gelmecha, Satyasis Mishra

“…This research bridges the gap between theoretical advancements in data-driven techniques and their practical deployment in real-world battery management systems.…”
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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

“…The present work investigates the estimation of state of charge (SoC) of Lithium Ion (Li-ion) batteries focussing on data-driven methodologies developed during the last five years. …”
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Data-driven deep learning model for predicting ambient temperature: environment and solar energy by Reza Hassanian, Nashmin Yeganeh, Ásdís Helgadóttir, Runar Unnthorsson, Morris Riedel

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