In this paper we present an approach for generation and initialization of fuzzy neural networks (FNN) from data. Fuzzy neural networks are concept that integrates some features of the fuzzy logic and the artificial neural networks theory. Based on analysis of several different fuzzy neural networks models, uniform representation method is presented, and two basic types are identified: FNN based...

Though traditional neural networks and fuzzy logic are powerful universal approximators, however without some refinements, they may not, in general, be good approximators for adaptive systems. By extending fuzzy sets to qualitative fuzzy sets, fuzzy logic may become universal approximators for adaptive systems. Similar considerations can be extended to neural networks.

This paper deals with the implementation of new proposed strategy for the reduction in the transient time of shunt active filter using intelligent controllers. Intelligent control is a class of control techniques that use various AI computing approaches like fuzzy logic, neural network, evolutionary computation, genetic algorithm etc. The proposed strategy works on the principle of energy of th...

Studies on the detection of early stage melanoma have recently gained significant interest. Computer aided diagnosis systems based neural networks, machine learning, convolutional networks (CNNs), and deep learning help considerably. The colour shapes images created by pixels are crucial for CNNs, as associated pictures interrelated just a person’s fingerprint is unique. By observing this relat...

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...

Fuzzy logic systems technology, particularly fuzzy control and fuzzy modeling techniques, is one of the most successful practical applications of fuzzy set and logic theory. In the past few years, the trend has been to combine fuzzy logic systems technology with artificial neural network technology to produce so called neural-fuzzy or fuzzy-neural systems. The objective is to take the advantage...

Abstract: This project report emphasis enhancement of power quality by using UPQC with fuzzy logic controller (FLC), Artificial Neural Network (ANN) controller and with the conventional proportionalintegral (PI) controller. The unified power quality conditioner (UPQC) is being used as a universal active power conditioning device to mitigate both current and voltage harmonics at a distribution s...

Active microwave remote sensing observations hold the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from microwave remote sensing techniques are typically complex because of the inherent difficulty in characterizing the interactions among land surface parameters that contribute to the retrieval process. Therefore adequate ...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...