Published February 1, 2017 | Version v1
Journal article

The application of the multi-alternative approach in active neural network models

  • 1. Voronezh State Technical University 14 Moscow Av., Voronezh, 394026 (Russian Federation)

Description

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/173/1/012012

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
173
Journal Issue
1
Journal Page Range
[8 p.]
ISSN
1757-899X

Conference

Title
5. international workshop on mathematical models and their applications
Dates
7-9 Nov 2016
Place
Krasnoyarsk (Russian Federation)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49077778
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
DISTRIBUTION; NEURAL NETWORKS; PROCESSING; STORAGE; STRUCTURAL MODELS