Artificial Neural Network (ANN) is a system loosely modeled on human brain. It tries to obtain a performance similar to that of human?s performance while solving problems. As a computational system it is made up of a large number of simple and highly interconnected processing elements which process information by its dynamic state response to external inputs. Computational elements in ANN are non-linear and so the results come out through non-linearity can be more accurate than other methods. These non-linear computational elements will be work ....etc

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Abstract
Identify some unique feature in the face image of a person, and then extract that Feature and compare. The system Extract eye from the face image and the extracted Image is given to input layer of artificial neural network. After three levels of processing, this network will generate a string which will be compared to the string earlier stored in the database for that face image. If the generated string of the current image already exists in the database, then it can be concluded that the image data is already enter ....etc

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Definition
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, thr ....etc

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INTRODUCTION

The importance of electricity in our day to day life has reached such a stage that it is very important to protect the power system equipments from damage and to ensure maximum continuity of supply. But there are power system blackouts by which the continuous power supply is being interrupted. What is more important in the case of a blackout is the rapidity with which the service is restored. Now- a -days power system blackouts are rare. But whenever they occur, the effect on commerce, in ....etc

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1. INTRODUCTION
This seminar is about the artificial neural network application in processing industry. An artificial neural network as a computing system is made up of a number of simple and highly interconnected processing elements, which processes information by its dynamic state response to external inputs. In recent times study of ANN models have gained rapid and increasing importance because of their potential to offer solutions to some of the problem ....etc

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AUTOCONFIGURING ARTIFICIAL NEURAL NETWORK APPLIED TO FAULT DIAGNOSIS IN POWER SYSTEMS

INTRODUCTION:
The fault diagnosis of a power system provides an effective means to
get information about system restoration and maintenance of the power
system. Artificial intelligence has been successfully implemented on
fault diagnosis and system monitoring. Expert systems are used by
defining rules, for a fault diagnosis. In the present work particularly
a new method of AI namely Artificial Neural Network is used ....etc

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ABSTRACT :


A fuzzy logic based adaptive power system stabilizer (PSS) is presented in this paper. The parameters of the fuzzy logic based PSS are tuned by neural networks. The system is divided into two subsystems, a recursive least square identifier with a variable forgetting factor for the generator and a fuzzy logic based adaptive controller to damp oscillations. The effectiveness of the proposed PSS in increasing the damping of local and inter area system; a two area 4 machine. The ANFIS PSS uses a zero order Sugeno type ....etc

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Definition
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, thr ....etc

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