The diploma thesis comprises of a general approach used to predict the time series, their categorization, basic characteristics and basic statistical methods for their prediction. Neural networks are also mentioned and their categorization with regards to the suitability for prediction of time series. A program for the prediction of the progress of multiple time series in stock market is designed and implemented, and it's based on a model of flexible neuron tree, whose structure is optimized using immune programming and parameters using a modified version of simulated annealing or particle swarm optimization. Firstly, the program is tested on its ability to predict simple time series and then on its ability to predict multiple time series.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:236567 |
Date | January 2012 |
Creators | Palček, Peter |
Contributors | Zbořil, František, Rozman, Jaroslav |
Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0019 seconds