introduction: the adaptive neuro-fuzzy inference system (anfis) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. in this study we used this model in breast cancer detection. methodology: a set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  first, the risk fact...

This paper compares the accuracy of three hybrid intelligent systems in forecasting ten international stock market indices; namely the CAC40, DAX, FTSE, Hang Seng, KOSPI, NASDAQ, NIKKEI, S&P500, Taiwan stock market price index, and the Canadian TSE. In particular, genetic algorithms (GA) are used to optimize the topology and parameters of the adaptive time delay neural networks (ATNN) and the t...

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated ...

Neuro-fuzzy inference systems have been used in many areas in civil engineering applications. A stability assessment model for epimetamorphic rock slopes has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS) for its capacity of dynamic nonlinear analyses. In the present study the inference system is employed to predict the stability of the slope by choosing bulk density γ, t...

The efficiency of a wind turbine highly depends on the value of tip speed ratio during its operation. The power coefficient of a wind turbine varies with tip speed ratio. For maximum power extraction, it is very important to hold the tip speed ratio at optimum value and operate the variable-speed wind turbine at its maximum power coefficient. In this paper, an intelligent learning based adaptiv...

the impact of air pollution and environmental issues on public health is one of the main topics studied in manycities around the world. ozone is a greenhouse gas that contributes to global climate. this study was conducted topredict and model ozone of yazd in the lower atmosphere by an adaptive neuro-fuzzy inference system (anfis). allthe data were extracted from 721 samples collected daily ove...

Parameters estimation; Induction motor; Squirrel-cage; Artificial neural network; Adaptive neuro-fuzzy inference system Abstract In the transient behavior analysis of a squirrel-cage induction motor, the parameters of the single-cage and double-cage models are studied. These parameters are usually hard to obtain. This paper presents two new methods to predict the induction motor parameters in t...

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. ...

Peak ground acceleration (PGA) plays an important role in assessing effects of earthquakes on the built environment, persons, and the natural environment. It is a basic parameter of seismic wave motion based on which earthquake resistant building design and construction are made. The level of damage is, among other factors, directly proportional to the severity of the ground acceleration, and i...

In this work a new method based on the adaptive neuro-fuzzy inference system (ANFIS) was successfully introduced to determine the characteristic parameters, effective permittivities and characteristic impedances, of conventional coplanar waveguides. The ANFIS has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid-learning algorithm,...