AEJ - Alexandria Engineering JournalSintering performance index can reflect the quality of sintered ore, and the level of sintered ore performance directly affects the stability of blast furnace production.
Aimin Yang
exaly +5 more sources
Tree-Based Machine Learning Models with Optuna in Predicting Impedance Values for Circuit Analysis
Micromachines, 2023 The transmission characteristics of the printed circuit board (PCB) ensure signal integrity and support the entire circuit system, with impedance matching being critical in the design of high-speed PCB circuits.
Ping-Feng Pai +2 more
exaly +4 more sources
Optimizing Depression Classification Using Combined Datasets and Hyperparameter Tuning with Optuna
SensorsThis research focuses on the depression states classification of EEG signals using the EEGNet model optimized with Optuna. The purpose was to increase model performance by combining data from healthy and depressed subjects, which ensured model robustness
Stefana Duta
exaly +6 more sources
Application of ADASYN and Optuna in the XGBoost Algorithm for Stunting Detection
Journal of Applied Informatics and ComputingThis study aims to develop an early detection model for childhood stunting risk using a machine learning approach based on Extreme Gradient Boosting (XGBoost), integrated with the Adaptive Synthetic Sampling (ADASYN) technique for data balancing and ...
Fastabyq Putra Sadewa, Defri Kurniawan
doaj +3 more sources
A Ship Trajectory Prediction Method Based on an Optuna–BILSTM Model
Applied SciencesIn the field of maritime traffic management, overcoming the challenges of low prediction accuracy and computational inefficiency in ship trajectory prediction is crucial for collision avoidance.
Yipeng Zhou, Ze Dong, Xiongguan Bao
doaj +3 more sources
Optimizing Multilayer Perceptron for Car Purchase Prediction with GridSearch and Optuna
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Multilayer Perceptron (MLP) is a powerful machine learning algorithm capable of modeling complex, non-linear relationships, making it suitable for predicting car purchasing power. However, its performance depends on hyperparameter tuning and data quality.
Ginanti Riski, Dedy Hartama, Solikhun
doaj +3 more sources
The Use of Machine Learning Models with Optuna in Disease Prediction
Electronics (Switzerland)Effectively and equitably allocating medical resources, particularly for minority groups, is a critical issue that warrants further investigation in rural hospitals. Machine learning techniques have gained significant traction and demonstrated strong performance across various fields in recent years.
Ping-Feng Pai +2 more
exaly +3 more sources
Fresh Meat Classification Using Laser-Induced Breakdown Spectroscopy Assisted by LightGBM and Optuna
FoodsTo enhance the accuracy of identifying fresh meat varieties using laser-induced breakdown spectroscopy (LIBS), we utilized the LightGBM model in combination with the Optuna algorithm.
Xiangyou Li
exaly +4 more sources
Federated Hyperparameter Optimisation with Flower and Optuna [PDF]
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023 Federated learning (FL) is an emerging distributed machine learning technique in which multiple clients collaborate to learn a model under the management of a central server. An FL system depends on a set of initial conditions (i.e., hyperparameters) that affect the system's performance.
Juan Marcelo Parra Ullauri +4 more
openaire +4 more sources
The Effect of SMOTE and Optuna Hyperparameter Optimization on TabNet Performance for Heart Disease Classification [PDF]
Jurnal SisfokomHeart disease is a medical condition affecting the cardiovascular system, disrupting blood circulation and reducing cardiac function efficiency, which can lead to severe health complications.
Danang Wijayanto +3 more
doaj +2 more sources