Results 111 to 120 of about 47,079 (313)

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Development of a Fully Optimized Convolutional Neural Network for Astrocytoma Classification in MRI Using Explainable Artificial Intelligence

open access: yesJournal of Imaging
Astrocytoma is the most common type of brain glioma and is classified by the World Health Organization into four grades, providing prognostic insights and guiding treatment decisions.
Christos Ch. Andrianos   +6 more
doaj   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

Boosting YOLO11: Global Attention & Hyperparameter Tuning for High-Fidelity Military Aircraft Detection

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Military aircraft detection from aerial and satellite imagery is crucial for strategic surveillance and intelligence. This study evaluated the impact of the Global Attention Mechanism (GAM) and hyperparameter optimization on the performance of the YOLO11
Satyo Widijanuarto, Ema Utami
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

TEGOA-CNN: An Improved Gannet Optimization Algorithm for CNN Hyperparameter Optimization in Remote Sensing Sence Classification

open access: yesRemote Sensing
The evolution of remote sensing technology has led to significant improvements in high-resolution and hyperspectral image acquisition, enhancing applications like environmental monitoring and disaster assessment.
Tsu-Yang Wu   +4 more
doaj   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

open access: yesAdvanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao   +9 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

open access: yesAdvanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li   +8 more
wiley   +1 more source

Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization

open access: yesCoRR
Bayesian optimization (BO) is a widely used approach to hyperparameter optimization (HPO). However, most existing HPO methods only incorporate expert knowledge during initialization, limiting practitioners' ability to influence the optimization process as new insights emerge. This limits the applicability of BO in iterative machine learning development
Lukas Fehring   +5 more
openaire   +2 more sources

A Hybrid Optimization Model for Transformer Fault Diagnosis Based on Gas Classification

open access: yesDigital
Dissolved gas analysis (DGA) provides valuable information for transformer condition monitoring, yet accurate multi-class fault identification remains challenging due to overlapping gas patterns and the sensitivity of classifier hyperparameters.
Junju Lai   +6 more
doaj   +1 more source

Home - About - Disclaimer - Privacy