Table of Contents
Advances in Artificial Neural Systems
Volume 2013, Article ID 962734, 12 pages
http://dx.doi.org/10.1155/2013/962734
Research Article

Fuzzified Data Based Neural Network Modeling for Health Assessment of Multistorey Shear Buildings

Department of Mathematics, National Institute of Technology Rourkela, Rourkela, Odisha 769 008, India

Received 21 November 2012; Revised 14 February 2013; Accepted 15 February 2013

Academic Editor: Matt Aitkenhead

Copyright © 2013 Deepti Moyi Sahoo and S. Chakraverty. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present study intends to propose identification methodologies for multistorey shear buildings using the powerful technique of Artificial Neural Network (ANN) models which can handle fuzzified data. Identification with crisp data is known, and also neural network method has already been used by various researchers for this case. Here, the input and output data may be in fuzzified form. This is because in general we may not get the corresponding input and output values exactly (in crisp form), but we have only the uncertain information of the data. This uncertain data is assumed in terms of fuzzy number, and the corresponding problem of system identification is investigated.