Results 81 to 90 of about 4,028 (199)

Classification of Alzheimer's Disease Using a Hybrid Technique Integration Between CNN and Optuna Optimization

NTU Journal of Engineering and Technology
Alzheimer's Disease (AD) is considered one of the most prevalent neurological disorders, primarily affecting elderly people and adversely impacting their brain functions. This disease is characterized by the gradual deterioration of cognitive functions,
Nawzt Sadiq Jaafar Al-Bayati, Raid Rafi Omar Al-Nima   +1 more
doaj   +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

Impact of Transported Wildfire Emissions on Urban PM2.5 and O3 in Queensland, Australia

Geophysical Research Letters, Volume 53, Issue 18, 28 September 2026.
Abstract Wildfires degrade urban air quality by transporting fine particulate matter (PM2.5 ${\text{PM}}_{2.5}$) and ozone (O3 ${\mathrm{O}}_{3}$) precursors. Such impacts are seldom quantified in the Southern Hemisphere. This study quantified contributions of wildfire emissions to ambient PM2.5 ${\text{PM}}_{2.5}$ and O3 ${\mathrm{O}}_{3}$ (ΔPM2.5 ...
Y. Xiao, S. Han, H. Zhang, H. Morton, P. Verma, Z. Ristovski, Z. Li, B. Wang   +7 more
wiley   +1 more source

The Use of Hyperparameter Tuning in Model Classification: A Scientific Work Area Identification

JOIV: International Journal on Informatics Visualization
This research aims to investigate the effectiveness of hyperparameter tuning, particularly using Optuna, in enhancing the classification performance of machine learning models on scientific work reviews. The study focuses on automating the classification
Nadya Alinda Rahmi, Sarjon Defit, - Okfalisa   +2 more
doaj   +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

Optimization of diabetes prediction methods based on combinatorial balancing algorithm

Nutrition & Diabetes
Background Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction.
HuiZhi Shao, Xiang Liu, DaShuai Zong, QingJun Song   +3 more
doaj   +1 more source

Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation

Underground Space
This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis ...
Yuxin Chen, Mohammad Hossein Kadkhodaei, Jian Zhou   +2 more
doaj   +1 more source

Optimized Breast Cancer Classification Using PCA-LASSO Feature Selection and Ensemble Learning Strategies With Optuna Optimization

IEEE Access
Breast cancer is one of the most prevalent and life-threatening diseases among women worldwide, making early and accurate detection crucial for effective treatment.
Prabhat Kumar Sahu, Taiyaba Fatma
doaj   +1 more source

Based on the WSP-Optuna-LightGBM model for wind power prediction

Journal of Physics: Conference Series
Abstract In order to optimize energy dispatch and enhance the predictive performance of wind power forecast, this study proposes a WSP-Optuna-LightGBM mixed regression prediction model based on wind speed-power curve (WSP), Optuna parameter optimization, and Light Gradient Boosting Machine (LightGBM).
Bo Xiang, Zhenqing Liu, Linhong Huang, Ming Qin   +3 more
openaire   +1 more source

Prediction of soil conditioner dosages for shield tunneling in sandy soil based on machine learning

Case Studies in Construction Materials
Inadequate soil conditioning during Earth Pressure Balance shield (EPBS) tunneling in sandy strata frequently causes operational issues. This study developed a data-driven framework integrating 15 operational and geological parameters from Shenyang Metro
Keqi Liu, Xueyi Liang, Wen Zhao, Xiumei Cao, Hezheng Pei   +4 more
doaj   +1 more source