Presentation	1996/3/18 Time Series Prediction Using Recurrent Neural Networks Ayumi Watanabe, Nobuo Morimura, Takeshi Nagano,
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Abstract(in English)	Neural nets are thought to be one of the useful solutions for time series prediction. In this paper, we propose a new neural net system for long term prediction. The proposed system is composed of the same number of basic modular recurrent neural nets as that of economic indexes and mutual connections between them at the hidden layer. It was shown by computer simulation that the system did good prediction in spite of it's relatively simple structure.
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Keyword(in English)	Recurrent Neural Networks / Prediction of economic indicators
Paper #	NC-95-118
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Conference Information
Committee	NC
Conference Date	1996/3/18(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Time Series Prediction Using Recurrent Neural Networks
Sub Title (in English)
Keyword(1)	Recurrent Neural Networks
Keyword(2)	Prediction of economic indicators
1st Author's Name	Ayumi Watanabe
1st Author's Affiliation	College of Engineering, Hosei University()
2nd Author's Name	Nobuo Morimura
2nd Author's Affiliation	College of Engineering, Hosei University
3rd Author's Name	Takeshi Nagano
3rd Author's Affiliation	College of Engineering, Hosei University
Date	1996/3/18
Paper #	NC-95-118
Volume (vol)	vol.95
Number (no)	598
Page	pp.pp.-
#Pages	8
Date of Issue