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http://bura.brunel.ac.uk/handle/2438/2393| Title: | Using intelligent optimization methods to improve the group method of data handling in time series prediction |
| Authors: | Abbod, MF Deshpande, K |
| Keywords: | GMDH;GA;PSO;Time series;Prediction;Finance |
| Issue Date: | 2008 |
| Publisher: | Springer |
| Citation: | The ICCS2008 International Conference on Computational Science: Advancing Science through Computation, Krakow, Poland, June 23-25, 2008 |
| Abstract: | In this paper we show how the performance of the basic algorithm of the Group Method of Data Handling (GMDH) can be improved using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The new improved GMDH is then used to predict currency exchange rates: the US Dollar to the Euros. The performance of the hybrid GMDHs are compared with that of the conventional GMDH. Two performance measures, the root mean squared error and the mean absolute percentage errors show that the hybrid GMDH algorithm gives more accurate predictions than the conventional GMDH algorithm. |
| URI: | http://bura.brunel.ac.uk/handle/2438/2393 |
| Appears in Collections: | Electronic and Computer Engineering Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Fulltext.pdf | 151.74 kB | Adobe PDF | View/Open |
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