Results 81 to 90 of about 2,998 (192)

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

Slope Stability Assessment Using an Optuna-TPE-Optimized CatBoost Model

Slope stability assessment is a critical component of engineering safety. Conventional analytical methods frequently struggle to integrate heterogeneous slope data and model intricate failure mechanisms, thereby constraining their efficacy in practical ...
Tao Ma, Chengliang Zhang, Tao Deng, Liangcheng Wang, Pei Shuai, Wei Wang   +5 more
core   +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

Using a hybrid attention mechanism as a method to improve the efficiency of network intrusion detection systems

Радіоелектронні і комп'ютерні системи
The subject matter of this article is a HybridAttention mechanism integrated into a deep neural architecture for Network Intrusion Detection Systems (NIDS). This study aims to develop and study a HybridAttention mechanism based on a combination of global
Andrii Nikitenko, Yevhen Bashkov
doaj   +3 more sources

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

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  

Fine-Tuning CNN-BiGRU for Intrusion Detection with SMOTE Optimization Using Optuna

Network security faces a significant challenge in developing effective models for intrusion detection within network systems. Network Intrusion Detection Systems (NIDS) are vital for protecting network traffic and preempting potential attacks by ...
BENCHAMA, Asmaa, ZEBBARA, Khalid
core   +3 more sources

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

Forecasting grocery item sales using gradient boosting models: A study of GridSearchCV, RandomizedSearchCV, and optuna optimization approaches

Ain Shams Engineering Journal
This study introduces predictive modeling based on Extreme Gradient Boosting (XGBoost), which utilizes Optuna for hyperparameter optimization and evaluates performance against GridSearchCV and RandomizedSearchCV using a 500-day dataset.
Puja Supakar, Mitali Sarkar, Biswajit Sarkar   +2 more
doaj   +1 more source