This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

This paper proposes a new intelligent scheme using type-2 fuzzy inference system in neural network structure. This type-2 fuzzy neural network system (type-2 FNN) combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). The general FNN system (called type-1 FNN system) has the properties of parallel computation scheme, easy to implement, fuzzy logic inference syst...

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 ...

This paper presents a comparative study of implementation of feature extraction and classification algorithms based on discrete wavelet decompositions and Adaptive Network Based Fuzzy Inference System (ANFIS) for digital modulation recognition. Here, in first stage, 20 different feature extraction methods are generated by separately using Daubechies, Biorthogonal, Coiflets, Symlets wavelet fami...

Wind generation is hectic by nature, making wind power forecasting highly challenging, particularly for short time frames. Forecasting of wind power is becoming progressively more important to power system operators and electricity market.Wind power is variable and irregular over various timescales as it is weather dependent. Thus precise forecasting of wind power is acknowledged as a major con...

This study aims to develop an Adaptive Network-based Fuzzy Inference System technique (ANFIS) and using the parameters of a complex mathematical model in the RO membrane performances. The ANFIS was constructed by using a subtractive clustering method to generate initial fuzzy inference systems. The model trained by 70% of the data set and then its validity is examined by remained 30% data set. ...

In this paper, an Adaptive-Network-based Fuzzy Inference System (ANFIS) is used for forecasting of natural gas consumption. It is clear that natural gas consumption prediction for future, surly can help Statesmen to decide more certain. There are many variables which effect on gas consumption but two variables that named Gross Domestic Product (GDP) and population, are selected as two input var...