REGULATION OF TRANSPORT SYSTEM BASED ON HEBB'S ALGORITHM

Abstract

The regulation of transport systems is crucial for effective traffic management, logistics, and supply chain optimization. This article explores the application of Hebb's algorithm, inspired by synaptic plasticity in the human brain, to control and optimize transport systems. We delve into the mathematical expression and initial conditions of Hebb's algorithm, discussing its potential in traffic management, route optimization, and resource allocation. We also address the challenge of unbalanced datasets in digit classification and propose a solution using Hebb's algorithm. Furthermore, we compare Hebb's algorithm with Kohonen's algorithm, highlighting their respective advantages. Ultimately, Hebb's algorithm offers a promising approach to enhance transport system regulation and traffic optimization based on neural network principles.