This paper presents the architecture and learning procedure underlying ANFIS (Adaptive-Network-based Fuzzy Inference System), a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data ...

Nowadays intelligent tools such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable methods for modeling an engineering system. This paper presents a new hybrid technique based on the combination of fuzzy inference system and artificial neural network for addressing navigational proble...

a multi objective honey bee mating optimization (hbmo) designed by online learning mechanism is proposed in this paper to optimize the double fuzzy-lead-lag (fll) stabilizer parameters in order to improve low-frequency oscillations in a multi machine power system. the proposed double fll stabilizer consists of a low pass filter and two fuzzy logic controllers whose parameters can be set by the ...

Motor fault detection and diagnosis involves processing a large amount of information of the motor system. With the combined synergy of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault detection/diagnosis process and successful fault detection/diagnosis schemes can be achieved. This paper presents two neural fuzzy (NN/FZ) inference systems, na...

The quantification and prediction of inter-agent dependency requirements is one of the main concerns in Agent Oriented Requirements Engineering. To evaluate exertion load of an agent within resource constraints, this work provides a comparative analysis of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). ANN is widely known due to its capability of learning the...

An 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 is presented in this paper. The capability of the proposed method (we named ANFIS2) for function approximation and dynamical system identification is remarkable. The structure o...

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 ...

allocation and removing of excess water from the irrigation and drainage network is one of the most important activities in the management of these networks. side weir is one of the most common structures for this purpose. study on the flow hydraulic characteristics of this structure included two parts, defining the water surface profiles and estimating the discharge coefficient. to estimate th...

The survey and modeling of the deformations of large structures is a major task in engineering geodesy. In this paper, a new procedure to describe and predict the deformations is presented and discussed which is based on Neuro-Fuzzy modeling. Neuro-Fuzzy methods are data driven; they deduce the model directly from the data. Hence, they are mostly convenient if there are no physical models avail...