Abstract: Fuzzy systems based on sparse rule bases produce the conclusion through approximation. This paper is the first part of a longer survey that aims to provide a qualitative view through the presentation of the basic ideas and characteristics of some methods and defining a general condition set brought together from an application-oriented point of view
Fuzzy rule interpolation (FRI) enables fuzzy inference systems to derive consequences when the obser...
A comparison is made of two approaches to approximate reasoning: Mamdani's interpolation method and ...
Fuzzy Rule Interpolation (FRI) provides a useful mechanism to derive reasonable approximate inferenc...
International audienceSeveral approaches have been proposed in the last few years for interpolating ...
Fuzzy inference systems provide a simple yet effective solution to complex non-linear problems, whic...
AbstractThe problem of sparse fuzzy rule bases is introduced. Because of the high computational comp...
[[sponsorship]]資訊科學研究所,資訊科技創新研究中心[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com...
The concept of fuzzy rule interpolation in sparse rule bases was introduced in 1993. It has become a...
This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy ru...
Approximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then rules in w...
Interpolative reasoning methods is a reasoning technique that is designed to deal with reasoning in ...
Fuzzy rule interpolation (FRI) offers a useful means for reducing the complexity of fuzzy models and...
International audienceThis paper proposes an approach to the interpolation between sparse fuzzy rule...
The design of effective rule based systems is a main goal of development in fuzzy logic and systems....
Abstract: Inference mechanisms and interpretations of fuzzy rule bases are studied together from the...
Fuzzy rule interpolation (FRI) enables fuzzy inference systems to derive consequences when the obser...
A comparison is made of two approaches to approximate reasoning: Mamdani's interpolation method and ...
Fuzzy Rule Interpolation (FRI) provides a useful mechanism to derive reasonable approximate inferenc...
International audienceSeveral approaches have been proposed in the last few years for interpolating ...
Fuzzy inference systems provide a simple yet effective solution to complex non-linear problems, whic...
AbstractThe problem of sparse fuzzy rule bases is introduced. Because of the high computational comp...
[[sponsorship]]資訊科學研究所,資訊科技創新研究中心[[note]]已出版;[SCI];有審查制度;具代表性[[note]]http://gateway.isiknowledge.com...
The concept of fuzzy rule interpolation in sparse rule bases was introduced in 1993. It has become a...
This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy ru...
Approximate reasoning systems facilitate fuzzy inference through activating fuzzy if–then rules in w...
Interpolative reasoning methods is a reasoning technique that is designed to deal with reasoning in ...
Fuzzy rule interpolation (FRI) offers a useful means for reducing the complexity of fuzzy models and...
International audienceThis paper proposes an approach to the interpolation between sparse fuzzy rule...
The design of effective rule based systems is a main goal of development in fuzzy logic and systems....
Abstract: Inference mechanisms and interpretations of fuzzy rule bases are studied together from the...
Fuzzy rule interpolation (FRI) enables fuzzy inference systems to derive consequences when the obser...
A comparison is made of two approaches to approximate reasoning: Mamdani's interpolation method and ...
Fuzzy Rule Interpolation (FRI) provides a useful mechanism to derive reasonable approximate inferenc...