Paper Abstract and Keywords |
Presentation |
2020-10-30 16:10
Solving the Parity Problem by Particle Multi-Swarm Optimization Hiroshi Sho (Kyutech) NC2020-24 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, the technology of particle swarm optimization is expanding remarkably. Especially, the technical development of particle multi-swarm optimization attracts attention, it is expected to solve difficult problems. In this paper, we propose the method which deals with pattern classification by using particle multi-swarm optimization. The basic idea, here, is to solve the parity problem using the search method of centralized and distributed intelligent particle multi-swarm optimization. To accomplish the task, increasing the number of bits of the parity problem and the addition of redundant neuro-units, which are the search target in computer experiments. From the obtained search results, the search characteristics and their changes are analyzed. Based on these experimental data, we clarified the search characteristics and performance effects of the used search methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
swarm intelligence / evolutionary computation / particle multi-swarm optimization / intelligent judgment / parity problem / neural networks / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 216, NC2020-24, pp. 83-88, Oct. 2020. |
Paper # |
NC2020-24 |
Date of Issue |
2020-10-22 (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) |
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NC2020-24 |
Conference Information |
Committee |
MBE NC NLP CAS |
Conference Date |
2020-10-29 - 2020-10-30 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
ME,NC,CAS,NLP |
Paper Information |
Registration To |
NC |
Conference Code |
2020-10-MBE-NC-NLP-CAS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Solving the Parity Problem by Particle Multi-Swarm Optimization |
Sub Title (in English) |
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swarm intelligence |
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evolutionary computation |
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particle multi-swarm optimization |
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intelligent judgment |
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parity problem |
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neural networks |
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1st Author's Name |
Hiroshi Sho |
1st Author's Affiliation |
Kyushu Institute of Technology (Kyutech) |
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Speaker |
Author-1 |
Date Time |
2020-10-30 16:10:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2020-24 |
Volume (vol) |
vol.120 |
Number (no) |
no.216 |
Page |
pp.83-88 |
#Pages |
6 |
Date of Issue |
2020-10-22 (NC) |
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