An Adaptative Neuro-Fuzzy Inference System (ANFIS) is developed to predict the acoustic form function (FF) for an infinite length cylindrical shell excited perpendicularly to its axis. The Wigner-Ville distribution (WVD) is used like a comparison tool between the calculated FF by the analytical method and that predicted by the neuro-fuzzy technique for a copper tube. During the application of t...

This article deals with utilization of the combination of the fuzzy system and artificial intelligence techniques, called the Adaptive Neuro Fuzzy Inference System ANFIS, with the aim to refine the diagnostic quality of the abdominal fetal electrocardiogram FECG. Within the scope of the experiments carried out and based on the ANFIS structure the authors created a complex system for removing th...

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 ...

In this paper, an attempt has been made to design an computational intelligence technique based expert system using Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting surface roughness in end milling of Inconel 718. Two different types of membership functions are adopted for analysis in ANFIS training and compared their differences regarding the accuracy rate of the surface roughness ...

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...

This paper proposes a hardware model that provides new fire detection and control mechanism with the interface of artificial neural network and fuzzy logic. This work is based on the integration of hardware module and implementation of artificial neural fuzzy inference system (ANFIS). The hardware consists of temperature sensor, smoke sensor, flame detector and a microcontroller unit. The senso...

This paper presents an original variable gain PI (VGPI) controller for speed control of a direct torque neuro fuzzy controlled (DTNFC) induction motor drive. First, a VGPI speed controller is designed to replace the classical PI controller in a conventional direct torque controlled induction motor drive. Its simulated performances are then compared to those of a classical PI controller. Then, a...

The flow in sewers is a complete three phase flow (air, water and sediment). The mechanism of sediment transport in sewers is very important. In other words, the passing flow must able to wash deposited sediments and the design should be done in an economic and optimized way. In this study, the sediment transport process in sewers is simulated using a hybrid model. In other words, using the Ada...