New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks

Georgiou, V; Pavlidis, N; Parsopoulos, K; Alevizos, P; Vrahatis, M

dc.contributor.author	Georgiou, V	en
dc.contributor.author	Pavlidis, N	en
dc.contributor.author	Parsopoulos, K	en
dc.contributor.author	Alevizos, P	en
dc.contributor.author	Vrahatis, M	en
dc.date.accessioned	2014-03-01T01:55:08Z
dc.date.available	2014-03-01T01:55:08Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/27611
dc.subject	particle swarm optimizer	en
dc.subject	Probabilistic Neural Network	en
dc.subject	Protein Localization	en
dc.subject	Sampling Technique	en
dc.subject	Statistical Test	en
dc.subject	Support Vector Machine	en
dc.subject	Feedforward Neural Network	en
dc.title	New Self-adaptive Probabilistic Neural Networks in Bioinformatic and Medical Tasks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1142/S0218213006002722	en
heal.identifier.secondary	http://dx.doi.org/10.1142/S0218213006002722	en
heal.publicationDate	2006	en
heal.abstract	We propose a self{adaptive probabilistic neural network model, which incorporates op- timization algorithms to determine its spread parameters. The performance of the pro- posed model is investigated on two protein localization problems, as well as on two medical diagnostic tasks. Experimental results are compared with that of feedforward neural networks and support vector machines. Dieren t sampling techniques are used	en
heal.journalName	International Journal on Artificial Intelligence Tools	en
dc.identifier.doi	10.1142/S0218213006002722	en