Results 31 to 40 of about 1,578 (156)

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

Using Deep Learning, Optuna, and Digital Images to Identify Necrotizing Fasciitis

Electronics (Switzerland)
Necrotizing fasciitis, which is categorized as a medical and surgical emergency, is a life-threatening soft tissue infection. Necrotizing fasciitis diagnosis primarily relies on computed tomography (CT), magnetic resonance imaging (MRI), ultrasound scans, surgical biopsy, blood tests, and expert knowledge from doctors or nurses.
Ming-Jr Tsai, Ping-Feng Pai, Lai Jung-Pin   +2 more
exaly   +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

Hyperparameter Tuning for Address Validation using Optuna

WSEAS TRANSACTIONS ON COMPUTER RESEARCH, 2023
Public institutions generally share personal information on their websites. That allows the possibility to find personal information when performing internet searches quickly. However, the personal information that is on the internet is not always accurate and can lead to misunderstandings and ambiguity concerning the accessible postal address ...
openaire   +3 more sources

Optimization of a New Adaptive Stacking Ensemble Model Integrated with IoT for Stress Level Detection Based on Physiological Signals

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Mental health issues among college students are receiving increasing attention, particularly because of academic and social pressures and the impact of technology use.
Muhardi, Mohd Rinaldi Amartha, Rika Melyanti, Yuda Irawan   +3 more
doaj   +1 more source

FuseLog: Fusing Symbolic and Temporal Dynamics for Enhanced Log Anomaly Detection

IEEE Access
Log-based anomaly detection is crucial for ensuring the reliability of large-scale distributed systems. DeepLog implemented a sequence-oriented methodology utilizing LSTMs, providing a data-driven substitute for rule-based techniques.
Ahmed Alzamil, Ramzi Guesmi, Tarek Gasmi, Ismail Marouani, Amer Alghadhban, Badr M. Alshammari, Tawfik Guesmi, Mohamed Khalil Fadhlaoui, Noamen Guermazi   +8 more
doaj   +1 more source