REGULATION OF TRANSPORT SYSTEM BASED ON HEBB'S ALGORITHM

Authors

  • Djurayev Sherzod Sobirjonovich Namangan Institute of Engineering and Technology
  • Fayzullayev Dedaxuja Zokirjon o`g`li Namangan Institute of Engineering and Technology

Keywords:

Regulation of transport systems, Traffic management, Logistics, Supply chain optimization, Hebb's algorithm, Synaptic plasticity, Mathematical expression, Initial conditions, Learning rate, Neuron representation, Weight initialization, Applications in transport system regulation, Unbalanced dataset, Classification of handwritten digits, Hebb's rule, Kohonen's algorithm, Supervised learning, Unsupervised learning, Neuron representation, Weight update, Output generation, Advantages of Hebb's algorithm, Advantages of Kohonen's algorithm, Linear relationship, Traffic flow estimation.

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.

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Published

2023-10-04

Issue

Vol. 2 No. 10 (2023)

Section

Articles

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