Prediction of gross domestic product development by frontal neural networks with learning process on the basic genetic and eugenic algorithms

Title:

Prediction of gross domestic product development by frontal neural networks with learning process on the basic genetic and eugenic algorithms

Creator:

Olej, Vladimír

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:e07911b4-3293-42ae-9c74-73dae8412c5b
uuid:e07911b4-3293-42ae-9c74-73dae8412c5b

Subject:

gross domestic product, econornic variables, prediction, frontal neural networks, genetic and eugenic algorithrns, and EuSANE algorithm

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The paper presents the possibility of application of frontal neural rietworks, genetic and eiigenic algorithrns in predicting gross domestic product development by designing a prediction model whose accuracy is superior to the model ušed in practice [1]. The learning process is implemented by means of a newly designed algorithm based on the EuSANE algorithm [2].

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2002 Volume:12 | Number:3

Harvested from:

CDK

Metadata only:

false