A Fick’s model that includes a Takagi-Sugeno fuzzy model to estimate the effective diffusivity was analyzed. The modelling of drying kinetics on mango trough this diffusional-fuzzy model was compared with the theoretical Fick’s model and the empirical Peleg and Weibull models. The identification and validation was performed from experimental drying curves of ripe mango slices (Mangifera indica ...

In this paper, an automatic text–independent Arabic word speaker identification system is presented using Fuzzy Wavelet Neural Network terminology (FWNN). The approach is combining wavelet theory to fuzzy logic and neural network which lead to fabricate a Fuzzy Wavenet . Position and dilation of the fuzzy wavenets are fixed and the weights are optimized according to learning algorithm in the ne...

The purpose of this article is twofold: first to introduce a multi attribute decision making model for radio frequency identification system consisting of four main criteria and five alternatives, and second to develop and solve the proposed fuzzy TOPSIS problem. Author presented an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ...

Identification of unknown system by training the parameters adaptively using different fuzzy models has been proven an interesting research area over last few decades. The objective of this paper is to identify a standard fuzzy system using different gradient methods and discuss their characteristics. Approach of this work is to calculate the gradient of the appropriate cost function to minimiz...

A Recurrent Trainable Neural Network (RTNN) with a two layer canonical architecture and a dynamic Backpropagation learning method are applied for local identification and local control of complex nonlinear plants. The RTNN model is incorporated in Hierarchical Fuzzy-Neural Multi-Model (HFNMM) architecture, combining the fuzzy model flexibility with the learning abilities of the RTNNs. A direct ...

An important limitation of fuzzy integrals for information fusion is the exponential growth of coefficients for an increasing number of information sources. To overcome this problem a variety of fuzzy measure identification algorithms has been proposed. HLMS is a simple gradient-based algorithm for fuzzy measure identification which suffers from some convergence problems. In this paper, two pro...

Fuzzy modeling has been widely applied as a powerful methodology for the identification of nonlinear systems from process measurements. In particular, the design of black-box approaches based on fuzzy models has been recognized as an alternative to mathematical methods. This article deals with the application of modeling and identification techniques for obtaining two fuzzy models of a solar do...

In this paper, we introduce a Takagi-Sugeno (TS) fuzzy model which is derived from a typical Multi-Layer Perceptron Neural Network (MLP NN). At first, it is shown that the considered MLP NN can be interpreted as a variety of TS fuzzy model. It is discussed that the utilized Membership Function (MF) in such TS fuzzy model, despite its flexible structure, has some major restrictions. After modify...

Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ...

Since the single input rule modules connected fuzzy inference model (SIRMs model) is proposed by Yubazaki, Yi et al., many researches on the extension of the SIRMs model have been reported. Moreover, the fuzzy functional SIRMs inference model, in which the consequent parts of the functional-type SIRMs model are generalized to fuzzy function, has proposed as one of various extension SIRMs models...