Mathematical Modeling based on Neural Network Learning for Object Recognition in Automated Systems
Year: 2024
Type: article
Abstract: This paper aims to identify efficient methods of mathematically modeling an automated physical system using a neural network. Based on the Levenberg-Marquardt method, we built a feed-forward neural network with the capabilities of a graphics accelerator. The model also sums up and suggests a new neural network training algorithm with Bayes regularization, Nguyen-Widrow initialization, and the early stopping and control method. This greatly expands the efficiency of solving problems where knowledge of an automation system is usable.
Authors: Ekaterina Gospodinova, Dimitar Nenov
Institution: Technical University of Sofia
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Technical University of Sofia
OpenAlex ID: W4407615638