Results 61 to 70 of about 211,846 (266)

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Loopy belief propagation and probabilistic image processing [PDF]

, 2003
Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method.
Inoue, J., Tanaka, K., Titterington, M.
core  

EDEN: Evolutionary Deep Networks for Efficient Machine Learning

, 2017
Deep neural networks continue to show improved performance with increasing depth, an encouraging trend that implies an explosion in the possible permutations of network architectures and hyperparameters for which there is little intuitive guidance.
Bassett, Bruce A., Dufourq, Emmanuel
core   +1 more source

Hyperparameter Tuning

This file contains hyperparameter tuning experiments.
  +4 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

An Enhanced Machine Learning Framework for Network Anomaly Detection

AI
Given the increasing volume and sophistication of cyber-attacks, there has always been a need for improved and adaptive real-time intrusion detection systems.
Oumaima Chentoufi, Mouad Choukhairi, Khalid Chougdali   +2 more
doaj   +1 more source

A Generic and Efficient Globalized Kernel Mapping-Based Small-Signal Behavioral Modeling for GaN HEMT

IEEE Access, 2020
The work reported in this article explores a novel Particle Swarm Optimization (PSO) tuned Support Vector Regression (SVR) based technique to develop the small-signal behavioral model for GaN High Electron Mobility Transistor (HEMT).
Ahmad Khusro, Saddam Husain, Mohammad S. Hashmi, Abdul Quaiyum Ansari, Sultangali Arzykulov   +4 more
doaj   +1 more source

Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes

Sensors, 2023
Modern active distribution networks (ADNs) witness increasing complexities that require efforts in control practices, including optimal reactive power dispatch (ORPD).
Tassneem Zamzam, Khaled Shaban, Ahmed Massoud   +2 more
doaj   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Sorghum crops classification and segmentation using shifted window transformer neural network and localization based on (YOLO)v9-path aggregation network

Frontiers in Plant Science
IntroductionThe world’s population has been increasing continuously, and this requires prompt action to ensure food security. One of the top five cereals produced worldwide, sorghum, is a staple of the diets of many developing nations.
Javaria Amin, Rida Zahra, Alena Maryum, Amber Sarwar, Amad Zafar, Seong-Han Kim   +5 more
doaj   +1 more source