| Grant number: | 13/08741-0 |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| Start date: | June 01, 2013 |
| End date: | May 31, 2014 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques |
| Principal Investigator: | Adriane Beatriz de Souza Serapião |
| Grantee: | Guilherme Sanchez Corrêa |
| Host Institution: | Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil |
Abstract Cluster analysis is a collection of unsupervised computational techniques often used in applications related to the patterns search, such as Data Mining. Clustering algorithms aim to separate objects into useful or significative groups (clusters), according to the objects features, so as to maximize the similarity of objects within a group and minimizing the similarity between objects of different groups, using a pre-defined metrics. This project aims to adapt a recent bioinspired optimization methods, called Fish School Search, to perform the numerical data clustering task. The proposal is to use this method along with the bioinspired approach for partitioning groups. Two different implementations to examine the clustering algorithm are proposed: one for sequential and one parallel CPU with GPU programming in CUDA environment, the results will be compared with each other to assess performance in the task of grouping data .. | |
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