In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed t...

Transformer fault diagnosis is an interesting subject for plant operators due to its criticality in power systems. There are several international standards available to interpret power transformer faults based on dissolved gas analysis. In certain cases these standards are not able to provide correct diagnosis. There are several soft computing techniques available for modelling transformer fau...

Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input-output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input-output data pairs. Good...

This paper presents a comprehensive study of ANFIS+ARIMA+IT2FLS models for forecasting the weather of Raipur, Chhattisgarh, India. For developing the models, ten year data (2000-2009) comprising daily average temperature (dry-wet), air pressure, and wind-speed etc. have been used. Adaptive Network Based Fuzzy Inference System (ANFIS) and Auto Regressive Moving Average (ARIMA) models based on In...

This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and...

This study investigates the ability of a new hybrid neuro-fuzzy model by combining (ANFIS) approach with marine predators’ algorithm (MPA) in predicting short-term (from 1 h ahead to day ahead) significant wave heights. Data from two stations, Cairns and Palm Beach buoy, were used assessing considered methods. The ANFIS-MPA was compared other methods, ANFIS genetic (ANFIS-GA) particle swarm opt...

The aim of this paper is to propose a procedure for model selection in Adaptive Neuro-Fuzzy Inference System (ANFIS) for time series forecasting. In this paper, we focus on the model selection based on statistical inference of R incremental. The selecting model is conducted by evaluating the inputs, number of membership functions and rules in architecture of ANFIS until the contribution of R2 i...

This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...