An innovative neural network approach for stock market prediction

This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysi...

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Veröffentlicht in:	The Journal of supercomputing Jg. 76; H. 3; S. 2098 - 2118
Hauptverfasser:	Pang, Xiongwen, Zhou, Yanqiang, Wang, Pan, Lin, Weiwei, Chang, Victor
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.03.2020 Springer Nature B.V
Schlagworte:	Algorithms Coders Compilers Computer Science Financial analysis Interpreters Machine learning Model accuracy Multimedia Neural networks Pricing Processor Architectures Programming Languages Securities markets Short term Stock exchanges Stock vector Automatic encoder Stock market prediction Long short-term memory neural network (LSTM neural network)
ISSN:	0920-8542, 1573-0484
Online-Zugang:	Volltext
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