Induction generator is the most common generator in wind energy systems because of its simplicity, ruggedness, little maintenance, price, etc. Thus, a novel design of an Adaptive Neuro-fuzzy Inference strategy(ANFIS) for analyzing some of the parameters such as frequency, voltage, current, etc. of the induction motor is presented in this paper. Induction motors are characterized by highly non-l...

In this work neural and neuro-fuzzy controllers are developed for the inverters of Uninterruptible Power Supplies (UPS) to improve their transient response and adaptability to various loads. Idealized load-currentfeedback controller is built to obtain example patterns for training the networks. Example patterns under various loading conditions are used in the off-line training of the selected n...

in the present work, the influences of temperature, solvent concentration and ultrasonic irradiation time were numerically analyzed on viscosity reduction of residue fuel oil (rfo). ultrasonic irradiation was applied at power of 280 w and low frequency of 24 khz. the main feature of this research is prediction and optimization of the kinematic viscosity data. the measured results of eighty-four...

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...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

Accurate solar radiation (SR) prediction is one of the essential prerequisites harvesting energy. The current study proposed a novel intelligence model through hybridization Adaptive Neuro-Fuzzy Inference System (ANFIS) with two metaheuristic optimization algorithms, Salp Swarm Algorithm (SSA) and Grasshopper Optimization (GOA) (ANFIS-muSG) for global SR at different locations North Dakota, USA...

This paper concentrated on the design and analysis of Neuro-Fuzzy controller based Adaptive Neuro-Fuzzy inference system (ANFIS) architecture for Load frequency control of interconnected areas, to regulate the frequency deviation and power deviations. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead ...

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed th...

Supplier selection is a key task for firms, enabling them to achieve the objectives of a supply chain. Selecting a supplier is based on multiple conflicting factors, such as quality and cost, which are represented by a multi-criteria description of the problem. In this article, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to overcome the supplier selection ...