Tsakonas, A., 2004. Towards neural-symbolic integration: the evolutionary neural logic networks. In: 2nd International IEEE Conference Intelligent Systems, 2004. Proceedings. IEEE, p. 156.
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This work presents the application of a new methodology for the production of neural logic networks into two real-world problems from the medical domain. Namely, we apply grammar guided genetic programming using cellular encoding for the representation of neural logic networks into population individuals. The application area is consisted of the diagnosis of diabetes and the diagnosis of the course of hepatitis patients. The system is proved able to generate arbitrarily connected and interpretable evolved solutions leading to potential knowledge extraction.
|Item Type:||Book Section|
|Additional Information:||22-24 June 2004|
|Uncontrolled Keywords:||cellular encoding , computational intelligence , diabetes diagnosis , evolutionary computation , grammar guided genetic programming , hepatitis diagnosis , hepatitis patients , knowledge extraction , neural logic networks , neural-symbolic integration|
|Subjects:||Technology > Engineering > Electrical and Electronic Engineering|
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||Dr Athanasios Tsakonas LEFT|
|Deposited On:||25 May 2011 16:53|
|Last Modified:||07 Mar 2013 15:44|
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