Results 91 to 100 of about 1,578 (156)

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

Joint Postprocessing of Air and Dew Point Temperature Ensemble Forecasts With Machine Learning

Meteorological Applications, Volume 33, Issue 5, September/October 2026.
This study compares two joint probabilistic postprocessing methods for calibrating air and dew point temperature ensemble forecasts. Results show that the bivariate distributional regression network improves uncertainty representation and overall forecast skill, highlighting its potential for operational meteorological applications. ABSTRACT Estimation
Enric Casellas, Josep‐Ramon Miró, Maria Cortès, Vicent Altava‐Ortiz, Jordi Moré   +4 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

Dual‐view scout scans with deep learning for ultra‐low dose attenuation correction in PET

Medical Physics, Volume 53, Issue 9, September 2026.
Abstract Background Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT‐based AC provides reliable attenuation (μ‐) maps but adds radiation, introduces PET/CT misalignment artifacts, and is unavailable on stand‐alone PET systems.
Florence M. Muller, Margaret E. Daube‐Witherspoon, Michael J. Parma, Amy E. Perkins, Peter B. Noël, Christian Vanhove, Stefaan Vandenberghe, Joel S. Karp   +7 more
wiley   +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

A Context‐Aware Decision Support Framework for Scientific Experiment Configuration

Software: Practice and Experience, Volume 56, Issue 9, Page 1100-1119, September 2026.
ABSTRACT Introduction Defining an experimental configuration is a complex decision problem for early‐stage researchers, who must map goals, constraints, and requirements onto datasets, algorithms, and parameter settings that directly affect experimental outcomes.
Pouriya Miri, Vlado Stankovski, Kristina Veljković, Petar Kochovski   +3 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

Climate Informed Dengue Prediction and Future Risk Under a Changing Monsoon Climate in Kerala, India

GeoHealth, Volume 10, Issue 9, September 2026.
Abstract Dengue fever has emerged as a major public health threat in India, with its burden projected to rise under climate change. This study investigates the influence of climate variability on dengue incidence in Kerala, a dengue hotspot in southern India, using 14 years of climate and dengue data (2006–2019).
Yacob Sophia, Mathew Koll Roxy, Surendranath Bindu Vaisakh, Pallipurathu Raghunathan Nair Sreelakshmi, Thekkumkara Surendran Anish, Pillaveetil Sathyadas Indu   +5 more
wiley   +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