The application of Artificial Intelligent approaches was introduced recently in protection of distribution networks. These approaches started with introducing Fuzzy Inference System (FIS), then using Artificial Neural Network (ANN).In this research, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) for protection of bus bars will be illustrated. The ANFIS can be viewed as a fuzzy...

The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normaland high-strength concrete was investigated. Results indicate that the proposed ANFIS modeling approach outperforms the other given models in terms of prediction capability. According to ...

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...

Electrical load forecasting is well-known as one of the most important challenges in the management of electrical supply and demand and has been studied extensively. Electrical load forecasting is conducted at different time scales from short-term, medium-term and long-term load forecasting. Adaptive neuro-fuzzy inference system is a model that combines fuzzy logic and adaptive neuro system and...

A new methodology for simulating the flow field inside an arteriovenous (AV) graft to vein anastomoses by the adaptive neuro fuzzy inference system (ANFIS) is presented in this study. For determining the optimal AV graft angle, an ANFIS-based model of neuro fuzzy-graft-vein (NF-GVEIN) is proposed. Therefore engineering design of the graft can be supported. The advantage of this neuro-fuzzy hybr...

Fuzzy inference systems have been applied in recent years in various medical fields due to their ability to obtain good results featuring white-box models. Adaptive Neuro-Fuzzy Inference System (ANFIS), which combines adaptive neural network capabilities with the fuzzy logic qualitative approach, has been previously used in modelling survival of breast cancer patients based on patient groups de...

Sedimentation in reservoirs is an important issue that should be considered for the reservoirs operation and useful life. In this study, application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) in prediction of the sediment release from the bottom outlet using semi-cylinder for different variables was evaluated. Dimensionless parameters such as dimens...

Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

A new speed control approach based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to a closed-loop, variable speed induction motor (IM) drive is proposed in this paper. ANFIS provides a nonlinear modeling of motor drive system and the motor speed can accurately track the reference signal. ANFIS has the advantages of employing expert knowledge from the fuzzy inference system and the learni...

Reinforced concrete beam; Shear strength; Artificial neural network; Adaptive neuro-fuzzy inference system; Iranian concrete institute code; American concrete institute code. Abstract In this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to predict the shear strength of Reinforced Concrete (RC) beams, and the models are compared with A...