Results 101 to 110 of about 2,584 (186)

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

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   +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

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

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  

Interpretable machine learning for predicting EUR of shale gas wells in the Weiyuan block

Scientific Reports
For shale gas development, it is essential to clarify the main controlling factors of EUR and realize its accurate prediction. Based on data from 123 wells in the Weiyuan block, this study combines Pearson correlation analysis, RF-RFE algorithm, and ...
Sijie He, Feifei Fang, Jin Chang, Xizhe Li, Ruilan Luo, Nijun Qi   +5 more
doaj   +1 more source

An Optuna-Based Metaheuristic Optimization Framework for Biomedical Image Analysis

Engineering, Technology & Applied Science Research
The success of Deep Learning (DL) in biomedical imaging heavily relies on optimal hyperparameter selection, which remains a complex and computationally intensive challenge. This paper introduces a metaheuristic-inspired Optuna framework for efficient hyperparameter optimization and validates its effectiveness using U-Net as a case study for brain MRI ...
openaire   +1 more source

Optuna ML Framework for SCBA Concrete Strength

International Journal of Concrete Structures and Materials
The cement industry plays a crucial role in global CO2 emissions. As demand for cement continues to rise, innovative solutions are required to mitigate its environmental impact.
Isaac Ajibola Fakoya, Abidemi Bashiru Folorunsho, Seungwon Kim, Cheolwoo Park   +3 more
doaj   +1 more source

GWtuna: Trawling through the data to find Gravitational Waves with Optuna and Jax

GWtuna is a fast gravitational-wave search prototype built on Optuna (optimisation software library) and JAX (accelerator-orientated array computation library) [1, 2]. Using Optuna, we introduce black box optimisation algorithms and evolutionary strategy algorithms to the gravitational-wave community.
Green, Susanna, Lundgren, Andrew
openaire   +2 more sources

Heart disease prediction using rough neutrosophic sets and dual-attention neural networks: RNS-OptiDANet. [PDF]

Front Artif Intell
Ashika T, Hannah Grace G.
europepmc   +1 more source