Results 31 to 40 of about 2,998 (192)

EPIC-NET: EEG-based epilepsy classification and brain localization using Optuna wave-gated recurrent unit network. [PDF]

Front Comput Neurosci
IntroductionEpilepsy is a chronic neurological disorder characterized by abnormal brain activity, often diagnosed through visual analysis of electroencephalography (EEG) signals.
Manjupriya R, Leema AA.
europepmc   +3 more sources

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

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

A Comparative Study of Hyperparameter Optimization for CatBoost: Random Search, Optuna, and Successive Halving

Journal of Applied Informatics and Computing
This study aims to evaluate the effectiveness of three hyperparameter optimization approaches Random Search, Successive Halving, and Optuna in the CatBoost algorithm for modeling individual income using the 2024 SAKERNAS data.
Claudian Tikulimbong Tangdilomban, Kusman Sadik, Aji Hamim Wigena   +2 more
doaj   +1 more source

AI-Driven Methane Emission Prediction in Rice Paddies: A Machine Learning and Explainability Framework

Methane
Rice cultivation accounts for roughly 10% of worldwide anthropogenic greenhouse gas emissions, making it a significant source of methane (CH4) Despite modest observational constraints, estimates of worldwide CH4 emissions from rice agriculture range from
Abira Sengupta, Fathima Nuzla Ismail, Shanika Amarasoma   +2 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Optimization of Scene and Material Parameters for the Generation of Synthetic Training Datasets for Machine Learning-Based Object Segmentation

Computers
Synthetic training data is often essential for neural-network-based segmentation when real datasets are difficult or impossible to obtain. Conventional synthetic data generation relies on manually selecting scene and material parameters. This can lead to
Malte Nagel, Kolja Hedrich, Nils Melchert, Lennart Hinz, Eduard Reithmeier   +4 more
doaj   +1 more source

OOG- Optuna Optimized GAN Sampling Technique for Tabular Imbalanced Malware Data

2022 IEEE International Conference on Big Data (Big Data), 2022
Cyberspace occupies a large portion of people's life in the age of modern technology, and while there are those who utilize it for good, there are also those who do not. Malware is an application whose construction was not motivated by a benign goal and it can harm, steal, or even alter personal information and secure applications and software.
S. M. Towhidul Islam Tonmoy, S. M. Mehedi Zaman   +1 more
openaire   +2 more sources

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Optuna-LightGBM : An Optuna hyperparameter optimization framework for the determination of solvent components in acid gas removal unit using LightGBM

Cleaner Engineering and Technology
Acid gas removal unit (AGRU) serves as an essential process in gas treatment, specifically designed to eliminate acid gases like hydrogen sulfide (H2S) and carbon dioxide (CO2) from natural gas. Absorption-based AGRU are extensively employing chemical solvents because of their strong performance and effectiveness.
Rafi Jusar Wishnuwardana, Madiah Binti Omar, Haslinda Binti Zabiri, Mochammad Faqih, Kishore Bingi, Rosdiazli Ibrahim   +5 more
openaire   +2 more sources