Fuzzified data based neural network modeling for health assessment of multistorey shear buildings

Authors:
Deepti Moyi Sahoo;S. Chakraverty
Affiliations:
Department of Mathematics, National Institute of Technology Rourkela, Rourkela, Odisha, India;Department of Mathematics, National Institute of Technology Rourkela, Rourkela, Odisha, India
Venue:
Advances in Artificial Neural Systems
Year:
2013

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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.