An Approach to Collaboration of Growing Self-Organizing Maps and Adaptive Resonance Theory Maps
Summary :
Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP).The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.9 pp.2047-2050
- Publication Date
- 2007/09/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e90-a.9.2047
- Type of Manuscript
- LETTER
- Category
- Neural Networks and Bioengineering
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Masaru TAKANASHI, Hiroyuki TORIKAI, Toshimichi SAITO, "An Approach to Collaboration of Growing Self-Organizing Maps and Adaptive Resonance Theory Maps" in IEICE TRANSACTIONS on Fundamentals,
vol. E90-A, no. 9, pp. 2047-2050, September 2007, doi: 10.1093/ietfec/e90-a.9.2047.
Abstract: Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP).The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.9.2047/_p
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@ARTICLE{e90-a_9_2047,
author={Masaru TAKANASHI, Hiroyuki TORIKAI, Toshimichi SAITO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Approach to Collaboration of Growing Self-Organizing Maps and Adaptive Resonance Theory Maps},
year={2007},
volume={E90-A},
number={9},
pages={2047-2050},
abstract={Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP).The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.},
keywords={},
doi={10.1093/ietfec/e90-a.9.2047},
ISSN={1745-1337},
month={September},}
Copy
TY - JOUR
TI - An Approach to Collaboration of Growing Self-Organizing Maps and Adaptive Resonance Theory Maps
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2047
EP - 2050
AU - Masaru TAKANASHI
AU - Hiroyuki TORIKAI
AU - Toshimichi SAITO
PY - 2007
DO - 10.1093/ietfec/e90-a.9.2047
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2007
AB - Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP).The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.
ER -
English
