Results 201 to 210 of about 103,221 (295)
Low-Cost IoT-Based Predictive Maintenance Using Vibration. [PDF]
Kolok P +4 more
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Logistics equipment condition monitoring and prediction based on digital twin and machine learning. [PDF]
Han F, Liu L, Sun J.
europepmc +1 more source
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
A Review of Fault Diagnosis Methods: From Traditional Machine Learning to Large Language Model Fusion Paradigm. [PDF]
Nie Q, Geng J, Liu C.
europepmc +1 more source
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan +8 more
wiley +1 more source
IHBA-optimized DR-SE-NPCNet for robust open-circuit fault diagnosis in three-level NPC inverters under mixed and noisy conditions. [PDF]
Liu Q, Chen C, Ouyang H, Xiao M, Lei W.
europepmc +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Enhancing reliability in electrical grids: A hybrid machine learning approach for electrical faults classification. [PDF]
Begum M +6 more
europepmc +1 more source

