Neuroevolutional Methods for Decision Support Under Uncertainty

Authors

Nina Komleva, Plekhanov Russian University of Economics - Moscow
Olga Khlopkova, Plekhanov Russian University of Economics - Moscow
Matthew He, Nova Southeastern UniversityFollow

Document Type

Article

Publication Date

2-28-2019

Publication Title

International Journal of Civil Engineering and Technology

Keywords

Neuroevolution, Evolutionary modeling, Neural networks, Genetic algorithms, Computational intelligence

ISSN

0976-6308

Volume

10

Issue/No.

2

First Page

1263

Last Page

1276

Abstract

The article presents a comparative analysis of the fundamental neuroevolutional methods, which are widely applied for the intellectualization of the decision making support systems under uncertainty. Based on this analysis the new neuroevolutionary method is introduced. It is intended to modify both the topology and the parameters of the neural network, and not to impose additional constraints on the individual. The results of the experimental evaluation of the performance of the methods based on the series of benchmark tasks of adaptive control, classification and restoration of damaged data are carried out. As criteria of the methods evaluation the number of failures and the total number of evolution epochs are used.

Comments

©IAEME Publication

NSUWorks Citation

Komleva, Nina; Khlopkova, Olga; and He, Matthew, "Neuroevolutional Methods for Decision Support Under Uncertainty" (2019). Mathematics Faculty Articles. 260.
https://nsuworks.nova.edu/math_facarticles/260