In this paper a new approach to fault diagnosis in an AC motor is introduced. This system combines a neuro-fuzzy system called FasArt (Fuzzy Adaptive System ART based) and the well-known fuzzy k nearest neighbor algorithm. A set of 15 types of non destructive faults has been tested, reaching a high degree of early fault detection and fault type recognition. Moreover, taking into account the neu...

The main goal of this research is to develop a novel optimum neuro-fuzzy system for diagnosis the complex and dynamic systems. .It has used the Particle Swarm Optimization (PSO) technique for training the Adaptive Neuro Fuzzy Inference System (ANFIS) off-line. The proposed system has applied for diagnosis the faults of two complex Photovoltaic (PV) systems. They are used to feed the power for l...

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy archi...

In industrial recirculating aquaculture, the feed required by fish accounts for a major part of total expenditure. this paper, multi-factor decision making system based on aggregation FIFFB feeding behavior, water temperature T environmental factors and biomass weight W was proposed to solve problem waste under traditional mode. To verify performance model, fuzzy inference FIS model is construc...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for USD/JPY exchange rates forecasting. Previous work often used time series techniques and neural networks (NN). ANFIS can be used to better explain solutions to users than completely black-box models, such as NN. The proposed neurofuzzy rule based system applies some technical and fundamental indexes as input variables. In o...

Decision making pertaining to injection profiles during oilfield development is one of the most important factors that affect the oilfields’ performance. Since injection profiles are affected by multiple geological and development factors, it is difficult to model their complicated, non-linear relationships using conventional approaches. In this paper, two adaptivenetwork-based fuzzy inference ...

A rule based signature verification system has been devised based on Adaptive Network Based Fuzzy Inference System (ANFIS). The histogram of the angle differences along the signature trajectory is used as a descriptor of the signatures. We partition the histogram to obtain a number of rules, which is limited to 4 at a time. The performance of the proposed system is found to be satisfactory on t...

in this paper, we propose a technique of artificial intelligence called adaptive neuro fuzzy inference system (anfis) for canceling maternal electrocardiogram (mecg) in fetal electrocardiogram extraction (fecg).this technique is used to estimate the mecg present in the abdominal signal of a pregnant woman. the fecg is then extracted by subtracting the estimated mecg from the abdominal signal. p...

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...