A new approach to fuzzy reasoning

@article{Weisbrod1998ANA,
  title={A new approach to fuzzy reasoning},
  author={Joachim Weisbrod},
  journal={Soft Computing},
  year={1998},
  volume={2},
  pages={89-99}
}
  • J. Weisbrod
  • Published 26 June 1998
  • Computer Science
  • Soft Computing
Abstract Over the last years fuzzy control has become a very popular and successful control paradigm. The basic idea of fuzzy control is to incorporate human expert knowledge. This expert knowledge is specified in a rule based manner on a high and granular level of abstraction. By using vague predicates a fuzzy rule base neglects useless details and concentrates on important relations. Following L.A. Zadeh’s famous principle of incompatibility, this technique is most promising when applied to… 

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References

SHOWING 1-10 OF 25 REFERENCES

On fuzzy implication relations

Detecting Local Inconsistency and Incompletenessin Fuzzy Rule

TLDR
The notion of {completeness and of {consistency} is introduced and a mechanism that is able to evaluate both degrees in the corresponding context is proposed that helps the designer to adjust the rule base in an appropriate way.

Fuzzy Logic in Control Systems : Fuzzy Logic

  • Computer Science
TLDR
Fuzzy implication functions, the sentence connectives and and also, compositional operators, inference mechanisms, and other concepts that are closely related to the decisionmaking logic of an FLC are investigated.

Fuzzy Control Revisited | Why Is It Working ?

TLDR
This paper introduces a complete and sound framework to explain the most common FC mechanism, Mamdani's original approach, and presents the idea of {distributions, which is a concept somewhat dual to possibility theory, and proves that regarding fuzzy sets as {Distributions means to postulate FC in the sense of M amdani.

Deductive approximate reasoning | a comparison of two approachesNicolaie

TLDR
This paper examines two complementary choices of deductive approximate reasoning, namely the Mamdani relation and the G odel relation, and presents empirical results with single rules, with groups of rules and rule chaining.

Outline of a New Approach to the Analysis of Complex Systems and Decision Processes

  • L. Zadeh
  • Computer Science
    IEEE Trans. Syst. Man Cybern.
  • 1973
TLDR
By relying on the use of linguistic variables and fuzzy algorithms, the approach provides an approximate and yet effective means of describing the behavior of systems which are too complex or too ill-defined to admit of precise mathematical analysis.

Combination of rules or their consequences in fuzzy expert systems

Processing in relational structures: fuzzy relational equations

FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I

TLDR
The fuzzy logic controller (FLC) based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy.