Results 11 to 20 of about 4,344 (219)
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, Mingyu Wu
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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
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Application of ADASYN and Optuna in the XGBoost Algorithm for Stunting Detection [PDF]
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
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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
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The Use of Machine Learning Models with Optuna in Disease Prediction
ElectronicsEffectively 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
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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 across datasets.
Stefana Duta
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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
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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
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Enhanced meta ensemble stacking approach with XGBoost and optuna based detection of Parkinson's disease [PDF]
Frontiers in Digital HealthParkinson's disease (PD), a progressive neurological disorder affecting motor function, has been significantly rising in prevalence in recent years. Current diagnostic methods, relying on clinical observations, neurological exams, and periodical DaTscan ...
Annsley Mohan Joseph Raj +2 more
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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