A fuzzy rule-based system design concentrates on accuracy and interpretability of the system. Fuzzy decision tree method is proposed based on fuzzy RDBMS and rule generation based on C4.5 algorithm known as fuzzy rule generation system (FRGS) algorithm. A fuzzy decision tree is developed by first converting a medical application of heart relational database to fuzzy heart relational database an...

to monitor the patient behavior, data are collected from patient’s body by a medical monitoring device so as to calculate the output using embedded software. incorrect calculations may endanger the patient’s life if the software fails to meet the patient’s requirements. accordingly, the veracity of the software behavior is a matter of concern in the medicine; moreover, the data collected from t...

The aim of this paper is to introduce a novel two-step Fuzzy Rule Interpolation Technique (FRIT) “VEIN”, based on the concept of Vague Environment. The strength of FRIT against classical fuzzy reasoning methods is the ability of gaining conclusion even in case where the knowledge is represented by sparse fuzzy rule bases. The FRIT “VEIN” introduced in this paper is following the structure the G...

Approximate fuzzy reasoning methods serves the task of inference in case of fuzzy systems built on sparse rule bases. This paper is a part of a longer survey that aims to provide a qualitative view through the various ideas and characteristics of interpolation based fuzzy reasoning methods. It also aims to define a general condition set for fuzzy rule interpolation methods brought together from...

Fuzzy rule based systems are increasingly being used to deal with time series processes that may lack stochastic stability due to non-stationarity, multiscaling and persistent autocorrelations. Wavelet filtering can be used to deal with such phenomenon. A method for creating a fuzzy-rule base from a time series, where the first difference (returns) of the preprocessed series is used, and high f...

Some difficulties emerging during the construction of fuzzy behaviour-based control structures are inherited from the type of the applied fuzzy reasoning. Classical fuzzy reasoning methods need a complete fuzzy rule base. In case of fetching fuzzy rules directly from expert knowledge e.g. for the behaviour coordination module, the way of building a complete rule base is not always straightforwa...

PLFC is a 0rst-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quanti0ers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded uni0cation among fuzzy constants. However, uni0cation for precise object constants is classical. In order to use PLFC for similarity-based reasoning, in this paper we extend a...

This paper addresses a robust fuzzy controller to damp low frequency oscillation following disturbances in power systems. In this research the fuzzy controller is used as a Power System Stabilizer (PSS) to improve the stability in power system. The rule base of the proposed PSS is optimized offline automatically by the improved Genetic Algorithm (GA). Usually in a rule base fuzzy control system...

In a large fuzzy rule-based system, a great dealof computation time is required for a fuzzy inference engine. A given fuzzy rule-based system is modeled as a fuzzy inference graph where each node in the graph corresponds to a relation representing a rule in the rule-based system. This paper presents algorithms to minimize the number of nodes in the graph using fuzzy operations as well as their ...