Name
Abstract | ||
|---|---|---|
Time series prediction is a problem with a wide range of applications, including energy systems planning, currency forecasting, stock exchange operations or traffic prediction. Accordingly, a number of different prediction approaches have been proposed such as linear models, Feedforward Neural network models, Recurrent Neural networks or Fuzzy Neural Models. In this paper one presents a prediction model based on fuzzy rules that relate past data values with the next unknown value to be estimated. A Fuzzy Boolean Neural Network has been used for that purpose and the laser data set of the Santa Fe contest has been used for illustration purpose. The results turned to be encouraging when compared with other published methods. |
Year | Venue | Keywords |
|---|---|---|
2005 | EUSFLAT Conf. | fuzzy neural nets.,time series prediction,recurrent neural network,feedforward neural network,linear model,neural network,stock exchange,prediction model,fuzzy,neural net |
DocType | Citations | PageRank |
Conference | 4 | 0.54 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jose A. B. Tome | 1 | 6 | 1.01 |
| João Paulo Carvalho | 2 | 110 | 17.52 |