نتایج جستجو برای: fuzzy feed back neural network ffnn

تعداد نتایج: 1103064  

Journal: :international journal of finance, accounting and economics studies 0
ali asghar anvary rostamy professor, accounting and finance department, faculty of management and economics, tarbiat modares university (tmu). nor addin mousazadeh abbasi master in accounting, faculty of management and economics, tarbiat modares university (tmu). mohammad ali aghaei assistant professor, accounting and finance department, faculty of management and economics, tarbiat modares university mahdi moradzadeh fard assistant professor, accounting and finance department, islamic azad university, karaj branch.

the jamor purpose of the present research is to predict the total stock market index of tehran stock exchange, using a combined method of wavelet transforms, fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.to do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

1993
Jelena Godjevac

This document describes the architecture of neuro fuzzy systems. First part of the document provides a review of general notions of fuzzy logic, and structure of fuzzy systems. A procedure and different types of fuzzy reasoning are described. The second part is devoted to the neural networks and to the simplest model of artificial neuron. In the third part, the similarities and differences betw...

2002
B. Karlik M. O. Tokhi M. Alci

This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classification accuracy of myoelectric signals using multi-layer perceptron with back-propagation algorithm, and the new fuzzy clustering neural network (FCNN) is presented. The myoelectri...

2004
F. QIU J. R. JENSEN

Neural networks, which make no assumption about data distribution, have achieved improved image classification results compared to traditional methods. Unfortunately, a neural network is generally perceived as being a ‘black box’. It is extremely difficult to document how specific classification decisions are reached. Fuzzy systems, on the other hand, have the capability to represent classifica...

2013
Tej Pal Singh

Face recognition technology has seen dramatic improvements in performance over the past decade, and such systems are now widely used for security and commercial applications. In this paper an improved approach has been used in which feed forward back propagation neural network is implemented through matlab. The results obtained shows that the proposed approach somewhat improves the performance ...

Journal: :journal of advances in computer research 0

security term in mobile ad hoc networks has several aspects because of the special specification of these networks. in this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy ratiocination of fuzzy system as...

2008
Chengfeng LUO Zhengjun Liu Wenli Meng

With a lot of successful applications of neural network-based classification, it has been recognized the classification can produce more accurate results than conventional approaches for remotely-sensed data. Although its training procedure is sensitive to the choice of initial network parameters and to over-fitting, the multilayer feed-forward networks trained by the back-propagation algorithm...

2013
Neha Gupta Harish Balaga D. N. Vishwakarma

This paper presents the use of ANN as a pattern classifier for differential protection of power transformer, which makes the discrimination among normal, magnetizing inrush, over-excitation, external fault and internal fault currents. The Back Propagation Neural Network Algorithm and Genetic Algorithm are used to train the multi-layered feed forward neural network and simulated results are comp...

2017
P. Kabal

This paper proposes to extend the band width of narrow band telephone speech signal by employing feed forward back propagation neural network. There are different types of faster training algorithm are available in the literature like Variable Learning Rate, Resilient Back propagation, Polak-Ribiére Conjugate Gradient , Conjugate Gradient with Powell/Beale Restarts , BFGS Quasi-Newton , One-Ste...

2016

This paper proposes to extend the band width of narrow band telephone speech signal by employing feed forward back propagation neural network. There are different types of faster training algorithm are available in the literature like Variable Learning Rate, Resilient Back propagation, Polak-Ribiére Conjugate Gradient , Conjugate Gradient with Powell/Beale Restarts , BFGS Quasi-Newton , One-Ste...

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