This paper proposes ajuzzy neural expert system (FNES) with the following two functions: (1) Generalization of the information derived from the training data and embodiment of knowledge in the form of the fuzzy neural network; (2) Extraction of fuzzy If-Then rules with linguistic relative importance of each proposition in an antecedent (I f -part) from a trained neural network. This paper also ...

the design and application of a fuzzy logic based controller to a leakage current relay waspresented in this paper. a novel approach based on fuzzy logic to form the tripping action of leakagecurrent relay was investigated. in addition to the theoretical aspect of fuzzy logic, detection of a leakagecurrent, measurement of the leakage current, determination of its duration, trip opening of fault...

The main feature of a Takagi-Sugeno (T-S) fuzzy model is to express the local dynamics of each fuzzy implication (rule) by a linear system model. The overall fuzzy model of the system is achieved by fuzzy “blending” of the linear system models. Parallel or feedback connections of T-S fuzzy systems which preserve the properties of each system are possible [1]. Thus a simple and straightforward a...

Fuzzy modeling of high-dimensional systems is a challenging topic. This paper proposes an effective approach to data-based fuzzy modeling of high-dimensional systems. An initial fuzzy rule system is generated based on the conclusion that optimal fuzzy rules cover extrema [8]. Redundant rules are removed based on a fuzzy similarity measure. Then, the structure and parameters of the fuzzy system ...

Edges characterize boundaries and are therefore considered for prime importance in image processing. Edge detection filters out useless data, noise and frequencies while preserving the important structural properties in an image. The proposed method adopts fuzzy reasoning in order to extract edges. Here the scanning of an image using the windowing technique takes place which is subjected to a s...

In this paper, a novel sliding mode control theory-based learning algorithm is proposed to train an interval type-2 fuzzy neural network using type-2 fuzzy triangular membership functions. The structure considered is a type-2 Takagi–Sugeno–Kang fuzzy logic system in which the antecedents are type-2 fuzzy sets, and consequents are crisp numbers (A2-C0). In the proposed learning algorithm, instea...

In this paper, we propose a novel fuzzy expert system for detection of Coronary Artery Disease, using cuckoo search algorithm. This system includes three phases: firstly, at the stage of fuzzy system design, a decision tree is used to extract if-then rules which provide the crisp rules required for Coronary Artery Disease detection. Secondly, the fuzzy system is formed by setting the intervals ...