Results 91 to 100 of about 4,087 (203)

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

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

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

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

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

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

KLASIFIKASI OBAT ANTI TUBERKULOSIS MENGGUNAKAN ALGORITMA CATEGORICAL BOOSTING DENGAN OPTIMASI OPTUNA [PDF]

Penyakit tuberkulosis merupakan salah satu penyebab utama kematian global, dengan angka kematian mencapai 1,30 juta jiwa pada tahun 2022, meningkat sebesar 3,2% dibandingkan tahun sebelumnya.
Harmoni, Yosua Satria Bara
core  

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

Application of FCEEMD-TSMFDE and adaptive CatBoost in fault diagnosis of complex variable condition bearings

Scientific Reports
The mode mixing problem and inherent mode function selection bias in Fast Ensemble Empirical Mode Decomposition (FEEMD) result in ineffective extraction of fault components during the denoising stage, the loss of coarse-grained information in Multiscale ...
Min Mao, Bingwei Xu, Yuhuan Sun, Kairong Tan, Yuran Wang, Chao Zhou, Chengjiang Zhou, Jingzong Yang   +7 more
doaj   +1 more source

KLASIFIKASI TINGKAT KEPARAHAN KECELAKAAN LALU LINTAS BERBASIS CATBOOST PADA DATA YANG TIDAK SEIMBANG MENGGUNAKAN SMOTENC DAN OPTUNA [PDF]

Traffic accidents represent a complex issue in Surabaya, having a significant impact on public safety and socio-economic loss. A primary challenge in accident severity classification modeling is the phenomenon of data imbalance, where slight injury cases
Ayatillah, Maslahatul Kaunaini
core