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Estimation of Multi-Pattern-to-Single-Pattern Functions by Combining Feedforward Neural Networks and Support Vector Machines

Pakka, Vijaynarasimha H and Thukararn, D and Khincha, HP (2004) Estimation of Multi-Pattern-to-Single-Pattern Functions by Combining Feedforward Neural Networks and Support Vector Machines. In: 2004 7th Seminar on Neural Network Applications in Electrical Engineering NEUREL, 23-25 September, Serbia,Montenegro, 273 -273.

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Abstract

In many fields there are situations encountered where a function has to be estimated to determine its output under new conditions. Some functions have one output corresponding to differing input patterns. Such types of function are difficult to map using a function approximation technique such as that employed by the multilayer perceptron networks. Hence to reduce this functional mapping to single pattern-to-single pattern type of condition, and then effectively estimate the function, we employ classification techniques such as the support vector machines. This paper describes in detail such a combined technique, which shows excellent results for a practical application in the field of power distribution systems.

Item Type: Conference Paper
Additional Information: �©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: FeedFomard Neural Networks;Support Vector Machines;Function Estimation
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 05 Dec 2005
Last Modified: 19 Sep 2010 04:21
URI: http://eprints.iisc.ernet.in/id/eprint/4258

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