Monitoring and predicting machine components' faults play an important role in maintenance actions. Developing an intelligent system is a good way to overcome the problems of maintenance management. In fact, several methods of fault diagnostics have been developed and applied effectively to identify the machine faults at an early stage using different quantities (Measures or Readings) such as c...

The output power delivered by solar photovoltaic (PV) module depends on weather conditions and to obtain maximum they are required to operate at maximum available power point for different weather conditions. Maximum power point tracking (MPPT) controllers are usually employed in PV power systems to extract maximum power. Since the solar PV module characteristics are highly nonlinear, conventio...

In this paper, an adaptive neuro fuzzy interference (ANFIS) based hybrid field oriented speed controlling of an induction motor is proposed. The proposed hybrid field oriented speed controller results attractive performance of induction motor with the potential features of both Artificial Neural network (ANN) and Fuzzy Logic Controller (FLC). In this topology the Artificial Neural Network (ANN)...

An Adaptative Neuro-Fuzzy Inference System (ANFIS), new flexible tool, is applied to predict the cut-off frequencies of the symmetric and the anti-symmetric circumferential waves (Si and Ai, i=1,2) propagating around an elastic aluminum cylindrical shell of various radius ratio b/a (a: outer radius and b: inner radius). The time-frequency of WignerVille and the proper modes theory are used in t...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

This paper presents to estimating studies of the torque data Electric Vehicle (EV) motor using Adaptive-Network Based Fuzzy Inference Systems (ANFIS). The real-time set Outer-Rotor Permanent Magnet Brushless DC (ORPMBLDC) which was designed and manufactured for in ultra-light EV, used these estimation process. current, power speed parameters are defined as input variables, parameter output vari...

In this paper, both the architecture and learning procedure underlying the parallel layer perceptron is presented. This topology, di1erent to the previous ones, uses parallel layers of perceptrons to map nonlinear input–output relationships. Comparisons between the parallel layer perceptron, multi-layer perceptron and ANFIS are included and show the e1ectiveness of the proposed topology. c © 20...

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...

This paper presents a new distance relay technique for transmission line protection by using well known control technique; Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS can be viewed either as a fuzzy system, a neural network or fuzzy neural network FNN. The structure is seen as a neural network for training and a fuzzy viewpoint is utilized to gain insight into the system and to sim...

Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influe...