Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus

dc.contributor.author	Win, Kay Thi
dc.contributor.author	Aye, Zin May
dc.date.accessioned	2019-08-06T10:44:12Z
dc.date.available	2019-08-06T10:44:12Z
dc.date.issued	2009-12-30
dc.identifier.uri	https://onlineresource.ucsy.edu.mm/handle/123456789/1883
dc.description.abstract	In this paper, an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely; Radial Basic Function (RBF) neural network. It uses relatively smaller number of locally tuned units and its adaptive in nature. RBFs are suitable for pattern recognition and classification. An artificial neural network with radial basic function is applied for the diagnosis of diabetes mellitus system This system consists of three phases: preprocessing, training and testing.	en_US
dc.language.iso	en	en_US
dc.publisher	Fourth Local Conference on Parallel and Soft Computing	en_US
dc.title	Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus	en_US
dc.type	Article	en_US