@article{ilie2012estimating,
  title = {Estimating the Romanian Economic Sentiment Indicator Using Artificial Intelligence Techniques},
  author = {Constantin Ilie and Margareta Ilie and Lucia Melnic and Ana-Maria Topalu},
  year = 2012,
  url = {https://ibimapublishing.com/articles/JEERBE/2012/966864/},
  journal = {Journal of Eastern Europe Research in Business and Economics},
  volume = (2012),
  pages = 22,
  doi = 10.5171/2012.966864,
  abstract = {The subject of the present paper represents the result of a research that uses artificial intelligence, through the artificial neural networks, in order to simulate the Romanian Economic Sentiment Indicator (ESI-mentioned by The Economist and provided by the European Commission — Economic and Financial Affairs website). The reason for the research is to determine a better method to forecast the Romania ESI considering its nonlinear behavior. For the simulation, a feed forward artificial neural network (ANN) was used. For this type of ANN, the best training algorithm is the back propagation algorithm. Training condition were set to a smaller than 5% error between the real data and the simulated data. The research is then extended to new input data (not available at the time of ANN training) used for comparison and forecasting of the real trends with the simulated ones. Even with new data, the use of the ANN determined forecasting results smaller than 5% (between -4.92; 5.16%). Also the ANN simulation offers an image about how indicators influence the ESI. In conclusion, the use of the ANN is considered a success and the authors determine the possibility that ANN research application be extended to other countries ESI or even to the European zone},
  keywords = {Artificial intelligence, Artificial Neural Network (ANN), Economic Sentiment Indicator.},
  note = Article ID: 966864
}