This paper presents the design and development of Neuro-Fuzzy controllers for the dc link current control in a two-terminal HVDC system. The dc link current error and its time derivative have been taken as the two inputs to the controller for deriving the control action, i.e., the firing angle of the converter. The basic structure of a Fuzzy controller has been modified to develop a Neuro-Fuzzy...

An adaptive neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet works. The ANFIS model was employed to calculate vent air discharge in different gate openings for an embankment dam. A hybrid learning algorithm obtained from combining back-propagation and least square estimate was adopted to identify linear and...

Abstract— This paper presents Neuro-Fuzzy logic based Power Conditioner for elimination of current harmonic. In it neuro-fuzzy based technique is used for generating compensating current to eliminate/reduce the harmonics content which is generated by the system. The modelling of Fuzzy rule base on Neural Network is also mention in this paper. FFT analysis also has been done for the calculation ...

Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answe...

Accurate estimation such as cost estimation, quality estimation and risk analysis is a major issue in management. We propose a patent pending soft computing framework to tackle this challenging problem. Our generic framework is independent of the nature and type of estimation. It consists of neural network, fuzzy logic, and an algorithmic estimation model. We made use of the Constructive Cost M...

Estimation of distribution algorithm for optimization of neural networks for intrusion detection system p. 9 Neural network implementation in reprogrammable FPGA devices-an example for MLP p. 19 A new approach for finding an optimal solution and regularization by learning dynamic momentum p. 29 Domain dynamics in optimization tasks p. 37 Nonlinear function learning by the normalized radial basi...

This paper presents an introduction to modelling the non-linear systems by using novel methods of Soft Computing. It lists the principal variants of soft computing. One of the wide areas of research related to hybrid systems in Soft Computing i.e., Neuro-Fuzzy method is focused and its methodology is specified.. Nuero-Fuzzy Systems are applied over various domains and resulted with accurate res...

Background and aims: Depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. So, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. Use of this memory is latent in synthetic neuro-fuzzy algorithm. P...

Accurate software development effort estimation is a critical part of software projects. Effective development of software is based on accurate effort estimation. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in ...

in a fuzzy metric space (x;m; *), where * is a continuous t-norm,a locally fuzzy contraction mapping is de ned. it is proved that any locally fuzzy contraction mapping is a global fuzzy contractive. also, if f satis es the locally fuzzy contractivity condition then it satis es the global fuzzy contrac-tivity condition.