### Abstract

A major issue in the field of fuzzy applications is the complexity of the algorithms used. In order to obtain efficient methods, it is necessary to reduce complexity without losing the easy interpretability of the components. One of the possibilities to achieve complexity reduction is to combine fuzzy rule interpolation with the use of hierarchical structured fuzzy rule bases, as proposed by Sugeno. As an interpolation method the KH interpolation is used, but other techniques are also suggested. The difficulty of applying this method is that it is often impossible to determine a partition of any subspace of the original state space so that in all elements of the partition the number of variables can be locally reduced. Instead of this, a sparse fuzzy partition is searched for and so the local reduction of dimensions will be usually possible. In this case however, interpolation in the sparse partition itself, i.e. interpolation in the meta-rule level is necessary. This paper describes a method how such a multi-level interpolation is possible.

Original language | English |
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Title of host publication | IEEE International Conference on Fuzzy Systems |

Publisher | IEEE |

Pages | 471-477 |

Number of pages | 7 |

Volume | 1 |

Publication status | Published - 2000 |

Event | FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA Duration: May 7 2000 → May 10 2000 |

### Other

Other | FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems |
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City | San Antonio, TX, USA |

Period | 5/7/00 → 5/10/00 |

### Fingerprint

### ASJC Scopus subject areas

- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality

### Cite this

*IEEE International Conference on Fuzzy Systems*(Vol. 1, pp. 471-477). IEEE.

**Interpolation in hierarchical fuzzy rule bases.** / Kóczy, L.; Hirota, Kaoru; Muresan, Leila.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE International Conference on Fuzzy Systems.*vol. 1, IEEE, pp. 471-477, FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems, San Antonio, TX, USA, 5/7/00.

}

TY - GEN

T1 - Interpolation in hierarchical fuzzy rule bases

AU - Kóczy, L.

AU - Hirota, Kaoru

AU - Muresan, Leila

PY - 2000

Y1 - 2000

N2 - A major issue in the field of fuzzy applications is the complexity of the algorithms used. In order to obtain efficient methods, it is necessary to reduce complexity without losing the easy interpretability of the components. One of the possibilities to achieve complexity reduction is to combine fuzzy rule interpolation with the use of hierarchical structured fuzzy rule bases, as proposed by Sugeno. As an interpolation method the KH interpolation is used, but other techniques are also suggested. The difficulty of applying this method is that it is often impossible to determine a partition of any subspace of the original state space so that in all elements of the partition the number of variables can be locally reduced. Instead of this, a sparse fuzzy partition is searched for and so the local reduction of dimensions will be usually possible. In this case however, interpolation in the sparse partition itself, i.e. interpolation in the meta-rule level is necessary. This paper describes a method how such a multi-level interpolation is possible.

AB - A major issue in the field of fuzzy applications is the complexity of the algorithms used. In order to obtain efficient methods, it is necessary to reduce complexity without losing the easy interpretability of the components. One of the possibilities to achieve complexity reduction is to combine fuzzy rule interpolation with the use of hierarchical structured fuzzy rule bases, as proposed by Sugeno. As an interpolation method the KH interpolation is used, but other techniques are also suggested. The difficulty of applying this method is that it is often impossible to determine a partition of any subspace of the original state space so that in all elements of the partition the number of variables can be locally reduced. Instead of this, a sparse fuzzy partition is searched for and so the local reduction of dimensions will be usually possible. In this case however, interpolation in the sparse partition itself, i.e. interpolation in the meta-rule level is necessary. This paper describes a method how such a multi-level interpolation is possible.

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M3 - Conference contribution

VL - 1

SP - 471

EP - 477

BT - IEEE International Conference on Fuzzy Systems

PB - IEEE

ER -