Um algoritmo de vida artificial para agrupamento de dados variantes no tempo
Tipo
Dissertação
Data de publicação
2012-09-14
Periódico
Citações (Scopus)
Autores
Santos, Diego Gadens dos
Orientador
Silva, Leandro Nunes de Castro
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Silva, Leandro Augusto da
Zuben, Fernando José Von
Zuben, Fernando José Von
Programa
Engenharia Elétrica
Resumo
Current technologies have made it possible to generate and store data in high volumes. To process and collect information in large databases is not always as easy as creating them. Therefore, this gap has stimulated the search for efficient techniques capable of extracting useful and non-trivial knowledge, which are intrinsic to these large data sets. The goal of this work is to propose a bioinspired algorithm, based on the Boids artificial life model, which will be used to group data in dynamic environments, i.e. in databases updated over time. The Bo-ids algorithm was originally created to illustrate the simulation of the coordinated movement observed in a flock of birds and other animals. Thus, to use this algorithm for data clustering, some modifications must be applied. These changes will be implemented in the classical rules of cohesion, separation and alignment of the Boids model in order to consider the distance (similarity/dissimilarity) among objects. Thus, it creates objects that stand and move around the space, representing the natural groups within the data, and it is expected that similar ob-jects tend to form dynamic clusters (groups) of Boids in the environment, while dissimilar objects tend to keep a larger distance between them. The results presented attest the robust-ness of the algorithm for clustering time-varying data under the light of different evaluation measures and in various databases from the literature.
Descrição
Palavras-chave
vida artificial , computação natural , mineração de dados , agrupamento de dados , boids , dados variantes no tempo , artificial life , natural computing , data mining , data clustering , boids , time-varying data
Assuntos Scopus
Citação
SANTOS, Diego Gadens dos. Um algoritmo de vida artificial para agrupamento de dados variantes no tempo. 2012. 92 f. Dissertação (Mestrado em Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo, 2012.