Results 21 to 30 of about 4,087 (203)

The Optuna–LightGBM–XGBoost Model: A Novel Approach for Estimating Carbon Emissions Based on the Electricity–Carbon Nexus

Applied Sciences
With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact.
Yuanhang Cai, Jianxin Feng, Yanqing Wang, Yuanming Ding, Yue Hu, Hui Fang   +5 more
doaj   +8 more sources

A Novel Identification Approach Using RFECV–Optuna–XGBoost for Assessing Surrounding Rock Grade of Tunnel Boring Machine Based on Tunneling Parameters

Applied Sciences (Switzerland)
In order to solve the problem of the poor adaptability of the TBM digging process to changes in geological conditions, a new TBM digging model is proposed.
Renyi Shi, Jianming Zhang
exaly   +3 more sources

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   +2 more sources

A novel dynamic Optuna hybrid Harris Hawks Optimization approach for classification of CAD. [PDF]

PLoS One
Coronary Artery Disease (CAD) is a leading cause of mortality worldwide and is primarily associated with atherosclerotic plaque formation, resulting in coronary artery stenosis.
Revathi CK, Santhi H.
europepmc   +2 more sources

Identity-Aware Lightweight MobileNetV2 with Distillation and Optuna for Face Spoofing Detection [PDF]

Edumatic
Presentation attacks, commonly known as face spoofing, remain a major security challenge in facial recognition-based authentication systems because forged media such as printed photos and replayed videos can deceive biometric verification.
Alif Sahputra, Alva Hendi Muhammad
doaj   +2 more sources

CO₂ Emission Prediction for Coal-Fired Power Plants by Random Forest-Recursive Feature Elimination-Deep Forest-Optuna Framework

Energies
As the greenhouse effect intensifies, China faces pressure to manage CO2 emissions. Coal-fired power plants are a major source of CO2 in China. Traditional CO2 emission accounting methods of power plants are deficient in computational efficiency and ...
Kezhi Tu, Yanfeng Wang, Xian Li, Xiangxi Wang, Zhenzhong Hu, Bo Luo, Liu Shi, Minghan Li, Guangqian Luo, Hong Yao   +9 more
doaj   +2 more sources

Enhancing Hepatitis C Diagnosis: The Impact of SMOTE, Optuna, and SHAP on Detection Methods [PDF]

Iranian Journal of Electrical and Electronic Engineering
Hepatitis C virus (HCV) detection is a critical aspect of early intervention and effective management of the disease. This paper presents a comprehensive study focused on enhancing the detection accuracy of HCV through the integration of advanced ...
S.M Mehzabeen, R Gayathri, Pattunnarajam Paramasaivam, Ramya A   +3 more
doaj   +1 more source

Optuna: Finding the optimal hyperparameters

, 2023
Application of Optuna to find the optimal hyperparameters for transfer learning or fine tuning the pre-trained models This code was used to find best hyperparameters to classify MS and Normal cases using SLO images. However it can be used in any other application.
Aghababaei Ali, Arian Roya, Kafieh Rahele   +2 more
openaire   +2 more sources

Optuna

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
The purpose of this study is to introduce new design-criteria for next-generation hyperparameter optimization software. The criteria we propose include (1) define-by-run API that allows users to construct the parameter search space dynamically, (2) efficient implementation of both searching and pruning strategies, and (3) easy-to-setup, versatile ...
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama   +4 more
openaire   +2 more sources

OPTUNA Optimization Based CNN-LSTM Model for Predicting Electric Power Consumption [PDF]

, 2020
Forecasting residential energy consumption using deep neural networks has been attempted in past researches. Typically, optimizing these networks relies on the operator’s prior knowledge.
Ekundayo, Ibidokun
core   +3 more sources