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Paper Abstract and Keywords
Presentation 2024-03-11 11:15
Topological Multi Reservoir Computing for Spatiotemporal Data Mining
Daisuke Takeda, Junya Kato, Ryo Natsuaki, Akira Hirose (UT) NC2023-45
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, advancements in sensor technology, Internet of Things (IoT) devices, high-speed mobile communication, and the development and widespread adoption of smartphone apps have made it possible to measure and collect various types of spatiotemporal data in real-time, everywhere.
Mining insights from spatiotemporal data is important to various application including population prediction.
Reservoir computing (RC) is capable of learning time-series information with computationally low-cost framework, and used for spatiotemporal data mining.
The use of multiple RC modules, known as Multi-RC (MRC) were also proposed for accurate prediction.
However, neural artificial intelligence should utilize data features to the maximum.
In this paper, we propose Topological Multi-RC (TMRC) for spatiotemporal data mining.
TMRC consists of RC modules cooperating with spatially adjacent modules to capture properties of spatiotemporal data.
We demonstrate the effectiveness of the TMRC through experiments of Geographical RC (GeoRC) which we propose to predict population in geographical space.
Keyword (in Japanese) (See Japanese page) 
(in English) reccurent neural network / reservoir computing / spatiotemporal data / multi reservoir computing / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 418, NC2023-45, pp. 13-18, March 2024.
Paper # NC2023-45 
Date of Issue 2024-03-04 (NC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NC2023-45

Conference Information
Committee NC MBE  
Conference Date 2024-03-11 - 2024-03-12 
Place (in Japanese) (See Japanese page) 
Place (in English) The Univ. of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Brain architecture, General 
Paper Information
Registration To NC 
Conference Code 2024-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Topological Multi Reservoir Computing for Spatiotemporal Data Mining 
Sub Title (in English)  
Keyword(1) reccurent neural network  
Keyword(2) reservoir computing  
Keyword(3) spatiotemporal data  
Keyword(4) multi reservoir computing  
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1st Author's Name Daisuke Takeda  
1st Author's Affiliation University of Tokyo (UT)
2nd Author's Name Junya Kato  
2nd Author's Affiliation University of Tokyo (UT)
3rd Author's Name Ryo Natsuaki  
3rd Author's Affiliation University of Tokyo (UT)
4th Author's Name Akira Hirose  
4th Author's Affiliation University of Tokyo (UT)
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Speaker Author-1 
Date Time 2024-03-11 11:15:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2023-45 
Volume (vol) vol.123 
Number (no) no.418 
Page pp.13-18 
#Pages 6 
Date of Issue 2024-03-04 (NC) 

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