Parallel fuzzy inference on hypercube computer

Sang Gu Lee*, Hee Hyol Lee, Michio Miyazaki, Kageo Akizuki


研究成果: Paper査読

1 被引用数 (Scopus)


In fuzzy database systems that have very large rules or fuzzy data, the inference time is much increased. Therefore, a high performance parallel fuzzy inference architecture is needed. In this paper, we propose a novel parallel fuzzy inference engine using Hypercube architecture. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. This architecture can be used in large expert systems or fuzzy database systems.

ページI-309 - I-314
出版ステータスPublished - 1999 12月 1
イベントProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 - Seoul, South Korea
継続期間: 1999 8月 221999 8月 25


OtherProceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99
CitySeoul, South Korea

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • 人工知能
  • 応用数学


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