Results 171 to 180 of about 92,424 (280)

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

SOH estimation for lithium-ion batteries using the distribution of relaxation time and feature optimized multilayer perceptron. [PDF]

iScience
Wang F, Liu S, Chen S, Zhang Q, Wang D, Ma X, Dai X.   +6 more
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Refining satellite Altimetry-Derived gravity anomaly model with shipborne gravity using multilayer perceptron neural networks. [PDF]

Sci Rep
Xiao C, Guo J, Zhu C, Li H, Liu S, Liu X.   +5 more
europepmc   +1 more source

Research on Deformation Prediction of Small Interval Tunnel Based on Machine Learning and Numerical Simulation

Energy Science &Engineering, EarlyView.
This study leverages machine learning algorithms—specifically artificial neural networks (ANN) and genetic programming (GP)—to forecast and analyze variations in vault settlement measurements during excavation of small interval tunnel. A settlement prediction model was developed and validated through comparative analysis with regression to evaluate the
Wenjie Zhai, Jia Xue, Yongjie Fu, Beichen Yu, Yan Zhu, Man Yuan, Mingbo Chi, Zhentao Li   +7 more
wiley   +1 more source

Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms. [PDF]

Medicine (Baltimore)
Chang YH, Kim HY, Yu IK, Kwak MY.
europepmc   +1 more source

Identifying Faults in Power Transformers Based on Machine‐Learning Algorithms Compared With Other Techniques

Energy Science &Engineering, EarlyView.
General framework of ensemble learning technique for transformer fault diagnostics compared with traditional dissolved gas analysis methods. ABSTRACT This paper implemented a comprehensive variety of modern machine‐learning techniques, which were demonstrated to be effective in handling complex tabular data, generating accurate predictions, and ...
Osama E. Gouda, Nourhan Ramadan, Matti Lehtonen, Mohamed M. F. Darwish   +3 more
wiley   +1 more source

Cross paradigm fusion of federated and continual learning on multilayer perceptron mixer architecture for incremental thoracic infection diagnosis. [PDF]

Sci Rep
Zhou T, Wang B.
europepmc   +1 more source

Application of GAN–CNN in Risk Assessment of Pipeline Failures in Multiphase Pipeline With Image Information Encoding Approach

Energy Science &Engineering, EarlyView.
Field data from multiphase pipelines are transformed into grayscale images via Image Information Encoding, preserving feature values and interparameter relationships. A GAN–CNN model generates synthetic images that are decoded to expand the original database.
Sihang Chen, Na Zhang, Biyuan Shui
wiley   +1 more source

OPTIMIZING MULTILAYER PERCEPTRON NEURAL NETWORK HYPERPARAMETERS

Journal of Process Management and New Technologies
Ivana PETKOVSKI
doaj   +1 more source