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Fuzzified Data Based Neural Network Modeling for Health Assessment of Multistorey Shear Buildings
Author(s) -
Deepti Moyi Sahoo,
Snehashish Chakraverty
Publication year - 2013
Publication title -
advances in artificial neural systems
Language(s) - English
Resource type - Journals
eISSN - 1687-7608
pISSN - 1687-7594
DOI - 10.1155/2013/962734
Subject(s) - artificial neural network , identification (biology) , data mining , computer science , fuzzy logic , artificial intelligence , machine learning , biology , botany
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

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