Probability and Possibility Automaton Learning Network
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- HIRASAWA Kotaro
- 九州大学
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- HARADA Masaaki
- 九州大学
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- OHBAYASHI Masanao
- 九州大学
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- MURATA Juuichi
- 九州大学
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- HU Jinglu
- 九州大学
Bibliographic Information
- Other Title
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- 確率分布・可能性分布を考慮したオートマトン学習ネットワーク
- カクリツ ブンプ カノウセイ ブンプ オ コウリョシタ オートマトン ガクシュ
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Description
Universal Learning Network(ULN) which is a generalized Neural Network, can be used to model and control large scale complicated systems. But ULN can not be applied to discrete event systems. Therefore a discrete event oriented learning network which is called Automaton Learning Network(ALN) has been already proposed. ALN has the same structure as ULN has. In this paper. a generalized type of ALN named Probability Automaton Learning Network(PrALN) and Possibility Automaton Learning Network(PoALN) are presented in order to realize an ALN with non-deterministic nature. In the simulations with a relatively simple model, we studied the fundamental characteristics of PrALN and PoALN.
Journal
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- IEEJ Transactions on Industry Applications
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IEEJ Transactions on Industry Applications 118 (3), 291-299, 1998
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204659900288
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- NII Article ID
- 10002726409
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- NII Book ID
- AN10012320
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- ISSN
- 13488163
- 09136339
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- NDL BIB ID
- 4413259
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed