This paper proposes a rule base compression method for fuzzy systems. The method is based on filtration of rules with identical linguistic values for the output that are known as non-monotonic rules. The filtration removes the redundant computations in the fuzzy inference with respect to the crisp values of the inputs to the fuzzy system. The method identifies the redundant rules after fuzzific...

This paper discusses fuzzy reasoning for approximately realizing nonlinear functions by a small number of fuzzy if-then rules with different specificity levels. Our fuzzy rule base is a mixture of general and specific rules, which overlap with each other in the input space. General rules work as default rules in our fuzzy rule base. First we briefly describe existing approaches to the handling ...

Fuzzy set theory allows for the inclusion of vague human assessments in computing problems. Also, it provides an effective means for conflict resolution of multiple criteria and better assessment of options. Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in sparse rule-based systems. However, in real-world applications of...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

Inference mechanisms and interpretations of fuzzy rule bases are studied together from the point of view of systems of fuzzy relation equations. A proper use of an inference mechanism connected to a fuzzy relation interpreting a fuzzy rule base is certified by keeping the fundamental interpolation condition. The paper aims at new solutions of systems of fuzzy relation equations which are motiva...

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...

Objective function based fuzzy clustering aims at nding a fuzzy partition by optimizing a function evaluating a (fuzzy) assignment of a given data set to clusters, that are characterized by a set of parameters, the so{called prototypes. The iterative optimization technique usually requires the objective function not only to be diierentiable, but prefers also an analytical solution for the equat...

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...