Results 91 to 100 of about 3,330 (201)

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

Temperature Prediction of Wet Clutch Friction Pair Based on Optuna-LSTM Neural Network

Applied Sciences
As critical actuating components in vehicular transmission systems, wet clutches exhibit strongly nonlinear thermal responses in their friction pairs during engagement operations.
Yuqi Yang, Chengyun Su, Zhifei Wang, Chao Zhou, Aolong Zhang   +4 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  

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

Optimizing Machine Learning Models for Urban Sciences: A Comparative Analysis of Hyperparameter Tuning Methods

Urban Science
Advancing urban scholarship and addressing pressing challenges such as gentrification, housing affordability, and urban sprawl require robust predictive models.
Tris Kee, Winky K.O. Ho
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  

Deep Learning Framework With Optuna-Based Hyperparameter Tuning for Predicting Dry Turning Process Performance of 42CrMo4 Steel

IEEE Access
This study presents an integrated experimental and data-driven modeling framework for predicting key machining responses such as tool wear (TW), material removal rate (MRR), and surface roughness (Ra) during dry turning of 42CrMo4 alloy steel ...
Vasanth Siva Kumar, Mogana Priya Chinnasamy, Swetha R Kumar   +2 more
doaj   +1 more source

Systematic Optimization of Ensemble Learning for Heart Failure Survival Prediction using SHAP and Optuna [PDF]

Heart failure (HF) stands as a major global health problem where precise and early prediction of patient prognosis is essential for improving clinical management and patient care.
Zaky, Umar, Setia, Bayu
core   +1 more source

Modified Prophet+Optuna Prediction Method for Sales Estimations

International Journal of Advanced Computer Science and Applications, 2022
Kohei Arai, Ikuya Fujikawa, Yusuke Nakagawa, Tatsuya Momozaki, Sayuri Ogawa   +4 more
openaire   +1 more source