Multi-dimensional raycasting for fuzzy pattern classification

Lanaridis, A; Stafylopatis, A

dc.contributor.author	Lanaridis, A	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:46:14Z
dc.date.available	2014-03-01T02:46:14Z
dc.date.issued	2009	en
dc.identifier.issn	10823409	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32622
dc.subject	Artificial Intelligent	en
dc.subject	Computer Game	en
dc.subject	High Dimensionality	en
dc.subject	Pattern Classification	en
dc.subject	Polar Coordinate	en
dc.subject	Multi Dimensional	en
dc.subject.other	Benchmark tests	en
dc.subject.other	Computer game	en
dc.subject.other	Fuzzy pattern classification	en
dc.subject.other	High dimensional spaces	en
dc.subject.other	Hyper-surfaces	en
dc.subject.other	Pattern classification	en
dc.subject.other	Polar coordinate	en
dc.subject.other	Raycasting	en
dc.subject.other	UCI repository	en
dc.subject.other	Computer programming	en
dc.subject.other	Equivalence classes	en
dc.subject.other	Pattern recognition systems	en
dc.subject.other	Artificial intelligence	en
dc.title	Multi-dimensional raycasting for fuzzy pattern classification	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICTAI.2009.66	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICTAI.2009.66	en
heal.identifier.secondary	5366372	en
heal.publicationDate	2009	en
heal.abstract	One of the most important problems in artificial intelligence, namely pattern classication, is essentially equivalent to finding hyper-surfaces seperating the different classes of data in a high-dimensional space. A method called raycasting is commonly used in computer game programming to locate and describe surfaces in a 2-dimesional map. A viewer, situated at some point on this map, casts rays of light towards various directions, and the rays extend until they hit a part of a surface. As a result, the surface can be described in polar coordinates as a set of vectors of varying lengths and angles. In this work we present a pattern classification system loosely based on the raycasting concept. We modify the method to create fuzzy pattern classification rules in 2 dimensions, and then generalize the rules to high-dimensional spaces. The resulting classifier is tested on a number of benchmark tests from the UCI Repository. © 2009 IEEE.	en
heal.journalName	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI	en
dc.identifier.doi	10.1109/ICTAI.2009.66	en
dc.identifier.spage	742	en
dc.identifier.epage	749	en