Clustering and Classification by Means of a Bee-Inspired Algorithm

• Grant number: 13/12005-7
• Support Opportunities: Scholarships in Brazil - Master
• Start date: September 01, 2013
• End date: June 30, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Leandro Nunes de Castro Silva
• Grantee: Dávila Patrícia Ferreira Cruz
• Host Institution: Escola de Engenharia (EE). Universidade Presbiteriana Mackenzie (UPM). Instituto Presbiteriano Mackenzie. São Paulo , SP, Brazil

Abstract

There is currently an overwhelming amount of data in different formats, from structured numeric databases to image data (unstructured data). This has been largely a consequence of the reduction in costs of digital artifacts and mobile communication. Thus, the development of tools to the retrieval and management of such data flood is becoming central in several decision making processes. Knowledge Discovery in Databases (KDD) is one of the fastest growing areas nowadays. At the same time, Natural Computing (NC) is one subarea of Computer Science and Engineering that has been achieving credibility due to its possibility of solving complex problems in different knowledge areas. The present research project brings together these two areas (KDD and NC) aiming at investigating and developing new bioinspired algorithms for the solution of complex data analysis problems. More specifically, some adaptations are proposed in a bee-inspired algorithm, called OptBees, for solving clustering and classification of numeric and image data. With this scope, this project will contribute to the scientific development of the field, the technological development by the proposition of algorithms directly applicable to practical problems, and for the graduation of a Master student.

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

FERREIRA CRUZ, DAVILA PATRICIA; MAIA, RENATO DOURADO; DA SILVA, LEANDRO AUGUSTO; DE CASTRO, LEANDRO NUNES. BeeRBF: A bee-inspired data clustering approach to design RBF neural network classifiers. Neurocomputing, v. 172, n. SI, p. 427-437, JAN 8 2016. (13/12005-7, 13/05757-2)

FERREIRA CRUZ, DAVILA PATRICIA; MAIA, RENATO DOURADO; DA SILVA, LEANDRO AUGUSTO; DE CASTRO, LEANDRO NUNES. BeeRBF: A bee-inspired data clustering approach to design RBF neural network classifiers. Neurocomputing, v. 172, p. 11-pg., 2016-01-08. (13/12005-7, 13/05757-2)

FERREIRA CRUZ, DAVILA PATRICIA; MAIA, RENATO DOURADO; DA SILVA, LEANDRO AUGUSTO; DE CASTRO, LEANDRO NUNES; OMATU, S; BERSINI, H; CORCHADO, JM; RODRIGUEZ, S; PAWLEWSKI, P; BUCCIARELLI, E. A Bee-Inspired Data Clustering Approach to Design RBF Neural Network Classifiers. DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 11TH INTERNATIONAL CONFERENCE, v. 290, p. 8-pg., 2014-01-01. (13/05757-2, 13/12005-7)

FERREIRA CRUZ, DAVILA PATRICIA; MAIA, RENATO DOURADO; DE CASTRO, LEANDRO NUNES; ENGELBRECHT, A; FILHO, CJAB; NETO, FBD. A New Encoding Scheme for a Bee-Inspired Optimal Data Clustering Algorithm. 2013 1ST BRICS COUNTRIES CONGRESS ON COMPUTATIONAL INTELLIGENCE AND 11TH BRAZILIAN CONGRESS ON COMPUTATIONAL INTELLIGENCE (BRICS-CCI & CBIC), v. N/A, p. 6-pg., 2013-01-01. (13/12005-7)