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Meta-heuristic-based optimization of probabilistic neural networks

Grant number: 15/50319-9
Support Opportunities:Regular Research Grants
Start date: August 01, 2016
End date: July 31, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Agreement: Ohio State University
Principal Investigator:João Paulo Papa
Grantee:João Paulo Papa
Principal researcher abroad: Hojjat Adeli
Institution abroad: Ohio State University, Columbus, United States
Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

In this proposal, we aim at modelling such task as a meta-heuristic-based - optimization problem by employing techniques based on swarm and evolutionary intelligence. The reason why using such techniques concern with their simplicity and very good results in several research areas. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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Scientific publications (5)
(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)
PEREIRA, DANILLO ROBERTO; PAPA, JOAO PAULO. A new approach to contextual learning using interval arithmetic and its applications for land-use classification. PATTERN RECOGNITION LETTERS, v. 83, n. 2, p. 188-194, . (15/50319-9, 14/16250-9)
TURESSON, HJALMAR K.; RIBEIRO, SIDARTA; PEREIRA, DANILLO R.; PAPA, JOAO P.; DE ALBUQUERQUE, VICTOR HUGO C.. Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations. PLoS One, v. 11, n. 9, . (14/16250-9, 13/07699-0, 15/50319-9)
PEREIRA, DANILLO ROBERTO; PAPA, JOAO PAULO. A new approach to contextual learning using interval arithmetic and its applications for land-use classification. PATTERN RECOGNITION LETTERS, v. 83, p. 7-pg., . (14/16250-9, 15/50319-9)
MARTINS, GUILHERME B.; PAPA, JOAO P.; ALMEIDA, JURANDY; IEEE. Temporal-and Spatial-Driven Video Summarization Using Optimum-Path Forest. 2016 29TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), v. N/A, p. 5-pg., . (14/16250-9, 15/50319-9)