Results 81 to 90 of about 1,578 (156)

A novel dynamic Optuna hybrid Harris Hawks Optimization approach for classification of CAD

Coronary Artery Disease (CAD) is a leading cause of mortality worldwide and is primarily associated with atherosclerotic plaque formation, resulting in coronary artery stenosis.
H. Santhi, C. K. Revathi
core   +1 more source

A Self‐Supervised Framework for Space Object Behaviour Characterisation

Expert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT Foundation Models, which leverage large neural networks pre‐trained on unlabelled data before fine‐tuning for specific tasks, are increasingly being applied to specialised domains. Recent examples include ClimaX for climate and Clay for satellite Earth observation, but a Foundation Model for Space Object Behavioural Analysis (SOBA) has not yet
Ian Groves, Andrew Campbell, James Fernandes, Diego Ramírez Rodríguez, Paul Murray, Massimiliano Vasile, Victoria Nockles   +6 more
wiley   +1 more source

Predicting Nepheline Formation in Nuclear Waste Glasses Using Machine Learning With Uncertainty Quantification

International Journal of Applied Glass Science, Volume 17, Issue 4, October 2026.
ABSTRACT The vitrification of high‐level waste (HLW) into borosilicate glass is a cornerstone of nuclear waste management, yet one of the key challenges in glass formulation for high‐aluminum‐containing waste streams is the precipitation of nepheline during the canister cooling stage.
Mayra Diaz‐Acevedo, Chloe E. Curry, Xiaonan Lu, Saehwa Chong, Sarah I. Allec, John D. Vienna   +5 more
wiley   +1 more source

Accurate Solution‐Phase Thermodynamics via Composite Quantum Chemistry and Machine Learning: Application to Biomass Decomposition

Journal of Computational Chemistry, Volume 47, Issue 23, September 5, 2026.
Thermodynamic quantities in the hydrated state are essential for understanding hydrothermal biomass decomposition. A general computational framework for evaluating accurate standard‐state solution‐phase thermodynamics of biomass compounds was developed.
Mikito Fujinami, Akihiko Okubo, Shuhei Ogo, Ayumu Onda, Hiromi Nakai   +4 more
wiley   +1 more source

MCH‐Guard: Multimodal machine learning framework for risk stratification of cerebral microhemorrhage risk in the Alzheimer's Disease Neuroimaging Initiative

Alzheimer's &Dementia, Volume 22, Issue 9, September 2026.
Abstract INTRODUCTION Efficient cerebral microhemorrhage (MCH) monitoring is critical for anti‐amyloid therapy safety due to amyloid‐related imaging abnormalities with hemosiderin deposition (ARIA‐H) risk. We developed MCH‐Guard, a multimodal machine‐learning framework, to stratify MCH risk for Alzheimer's Disease Neuroimaging Initiaitive (ADNI ...
Alper Gel, Eliana Phillips, Isabella Hausle, Pamela Thropp, Duygu Tosun, for the Alzheimer's Disease Neuroimaging Initiative   +5 more
wiley   +1 more source

Optuna Tuning Results PPO Reinforcement Learning Hyperparameters Performance

Systematic hyperparameter tuning using Optuna was expected to improve PPO model performance in a multi-microgrid environment. We hypothesized that optimizing hyperparameters like learning rate and network architecture would enhance model performance ...
Messlem, A (via Mendeley Data)
core   +1 more source

An integrated machine learning and hyperparameter optimization framework for noninvasive creatinine estimation using photoplethysmography signals

Healthcare Analytics
Frequent measurement of creatinine levels is vital for patients with chronic kidney disease. Traditional creatinine level measurement requires invasive blood test which has several disadvantages like discomfort, anxiety, panic, pain, risk of infection ...
Parama Sridevi, Zawad Arefin, Sheikh Iqbal Ahamed   +2 more
doaj   +1 more source

Safety soft sensor development for pilot‐scale ilmenite electric arc furnace using long short‐term memory‐based architecture

The Canadian Journal of Chemical Engineering, Volume 104, Issue 9, Page 4702-4718, September 2026.
Abstract Ilmenite electric arc furnaces (EAFs) are used for smelting titanium‐iron oxide ore at high temperatures generated by electrical arcs to produce titanium slag and pig iron. As these units are pushed to their limits, ensuring safe and reliable operation becomes challenging.
Antony Gareau‐Lajoie, Djogap F. Chrysler J., Daniel Rodrigues, Marie‐Ève Gosselin, Moncef Chioua   +4 more
wiley   +1 more source

Prediksi Laju Inflasi di Jawa Timur Menggunakan Model N-BEATS dan Optimasi Optuna: Prediction of Inflation Rate in East Java Using the N-BEATS Model and Optuna Optimization

Inflasi merupakan indikator penting yang memengaruhi kestabilan dan pertumbuhan ekonomi suatu wilayah. Prediksi inflasi yang akurat sangat dibutuhkan guna mendukung perumusan kebijakan ekonomi yang tepat.
Trimono, Trimono, Riswanda, Mohammad Nizar, Saputra, Wahyu Syaifullah Jauharis   +2 more
core   +1 more source

Unraveling the Spatiotemporal Dynamics and Nonlinear Drivers of Green Transition of Farmland Use in Major Grain‐Producing Areas: A Case Study of Jiangsu Province, China

Land Degradation &Development, Volume 37, Issue 15, Page 10851-10872, September 2026.
ABSTRACT Promoting the green transition of farmland use (GTFU) in major grain‐producing areas is essential for ensuring food security and advancing sustainable agricultural development. However, existing studies on GTFU have predominantly relied on static cross‐sectional analyses, with insufficient attention paid to its nonlinear driving mechanisms. To
Zhixian Sun, Yixuan Lu, Xinyue Zheng, Dongmei Zhang, Yian Xu, Guanxin Yao   +5 more
wiley   +1 more source