Abstract
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.
| Original language | English |
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| Pages | I-309 - I-314 |
| Publication status | Published - 1999 Dec 1 |
| Externally published | Yes |
| Event | Proceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 - Seoul, South Korea Duration: 1999 Aug 22 → 1999 Aug 25 |
Other
| Other | Proceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 |
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| City | Seoul, South Korea |
| Period | 99/8/22 → 99/8/25 |
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Artificial Intelligence
- Applied Mathematics