| Paper title: |
Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process |
| Published in: | Issue 2, (Vol. 2) / 2008 |
| Pages: | 9-13 |
| Author(s): | Balan Ionut, Morariu Nicolae |
| Abstract. | 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. |
| Keywords: | Forecasting, Neural Networks, Genetic Algorithms, Artificial Intelligence, Random, Population, Offsprings, Reproduction, Mutation |
| References: | 1. Dumitrescu, D., Principiile inteligenţei artificiale,Ed. Albastră, 2002 2. Haykin, S., Neural Networks – A Comprehensive foundation- Second Edition, Prentice Hall International, Inc., 1999 3. Fausett, L., Fundamentals of neural networksArchitectures, Algorithms, and Applications, Prentice Hall, 1994 4. Valluru, B. R., C++ Neural Networks and Fuzzy Logic, MT Books, 1995 5. Vlad, S., Morariu N., The prediction of chaotic time series using neural networks , 2nd Romanian Hungarian joint symposium on applied computational intelligence, SACI 2005 6. Dumitrescu, D., Algoritmi genetici,Ed. Albastră, 2002 7. Sen, Z., Oztopal, A., Genetic algorithms for the classification and prediction of precipitation occurrence, Hydrological Sciences-Journal, 46(2), 2001 |
| Back to the journal content | |
