GPU accelerated genetic clustering

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084885" target="_blank" >RIV/61989100:27240/12:86084885 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-34859-4_41" target="_blank" >http://dx.doi.org/10.1007/978-3-642-34859-4_41</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-34859-4_41" target="_blank" >10.1007/978-3-642-34859-4_41</a>

Result language
angličtina
Original language name
GPU accelerated genetic clustering
Original language description
Genetic and evolutionary algorithms have been used to find clusters in data with success. Unfortunately, evolutionary clustering suffers from the high computational costs when it comes to fitness function evaluation. The GPU computing is a recent programming and development paradigm introducing high performance parallel computing to general audience. This study presents a design, implementation, and evaluation of a genetic algorithm for density based clustering for the nVidia CUDA platform.
Czech name
—
Czech description
—

Project
<a href="/en/project/FR-TI1%2F420" target="_blank" >FR-TI1/420: *Integrated software system for optimalization and control of technological processes and prediction of production quality for large technological complexes with use of advanced mathematic method, simulation and artificial intelligence.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)