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 attempts to apply an adaptive network-based fuzzy inference system (ANFIS) for analysis of the resonant frequency of a single-layer single-patch microstrip rectangular patch antenna with two equal size slots which are placed on the patch in the form of parallel to resonance edges. The resonant frequency is calculated as the position of the slots is shifted from the right endpoint to ...

Fuzzy Neural Networks (FNNs) techniques have been effectively used in applications that range from medical to mechanical engineering, to business and economics. Despite of attracting researchers in recent years and outperforming other fuzzy systems, Adaptive Neuro-Fuzzy Inference System (ANFIS) still needs effective parameter training and rulebase optimization methods to perform efficiently whe...

Brushless DC (BLDC) motors are the most popular used by industry because they easy to control. BLDC generally controlled artificial controls such as Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). However, performance of control system in previous studies was compared separately with their respective parameters, making it difficu...

Forecasting reservoir inflow is important to hydropower reservoir management and scheduling. An Adaptive-Network-based Fuzzy Inference System (ANFIS) is successfully developed to forecast the long-term discharges in Manwan Hydropower. Using the long-term observations of discharges of monthly river flow discharges during 1953-2003, different types of membership functions and antecedent input flo...

This paper presents an optimal load balancing algorithm based on both of the ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling and the FIS (Fuzzy Inference System) for the local status of real servers. It also shows the substantial benefits such as the removal of loadscheduling overhead, QoS (Quality of Service) provisioning and providing highly available servers, provided by the suggested...

The ANFIS is the product of two methods, neural networks, and fuzzy systems. If both these intelligent methods are combined, better reasoning will be obtained in term of quality and quantity. In other words, both fuzzy reasoning and neural network calculation will be available simultaneously [7]. This ANFIS technique has been successfully applied by many researchers for sensor-based autonomous ...

this paper presents a new strategy based on multi-stage fuzzy (msf) pid controller based on artificial bee colony (abc) for damping power system stabilizer (pss) in multi-machine environment. the recent studies in artificial intelligence demonstrated that the abc optimization is strong intelligent method in complicated stability problems. also, finding the parameters of pid controller in power ...

In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of electrocardiographic changes in patients with partial epilepsy. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Two...

The aim of this study was to employ iota-carrageenan (IC) and wheat protein (WP) as an emulsifier alternative to egg yolk in a model mayonnaise system. A solution of 0.1% IC and 4% WP was prepared and used as an emulsifier in five different mayonnaise formulas. All mayonnaise treatments were evaluated and compared based on emulsion stability and viscosity at 4, 23, and 40 C. In addition, an ada...