Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process

Autor:	Nicolae Morariu, Ionut Balan
Jazyk:	angličtina
Rok vydání:	2008
Předmět:	forecasting neural networks genetic algorithms artificial intelligence random population offsprings reproduction mutation Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Journal of Applied Computer Science & Mathematics, Vol 2, Iss 4, Pp 9-13 (2008)
Druh dokumentu:	article
ISSN:	2066-4273 2066-3129
Popis:	This paper aims to describe the implementa-tion of a neural network and a genetic algorithm system in order to forecast certain economic indicators of a free market economy. In a free market economy forecasting process precedes the economic planning (a management function), providing important information for the result of the last process. Forecasting represents a starting point in setting of target for a firm, an organization or even a branch of the economy. Thus, the forecasting method used can influence in a significant mode the evolution of an entity. In the following we will describe the forecasting of an economic indicator using two intelligent systems. The difference between the results obtained by this two systems are described in chapter IV.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/1ee679b0ab7a4cab92d0ed3dcb22c2ca Zobrazit plný text záznamu View record in DOAJ