NEURAL NETWORK MODELS FOR PREDICTION OF STOCK MARKET DATA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63468352%3A_____%2F11%3A%230000134" target="_blank" >RIV/63468352:_____/11:#0000134 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
NEURAL NETWORK MODELS FOR PREDICTION OF STOCK MARKET DATA
Original language description
The article deals the possibility of using neural networks for data prediction. These data represent the values of the shares on the NASDAQ stock market and are used as training set of neural networks. In preparing model we use multiple time series. These series create a single test set compiled using the PHP language. To implementation the SNNS (Stuttgart Neural Network Simulator) simulator used in the Java version, which allows selection of different options for learning to achieve good values of global error.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů