Now showing items 1-10 of 140
Análise comparativa de técnicas avançadas de agrupamento
(Universidade Federal de São CarlosUFSCarPrograma de Pós-graduação em Ciência da Computação (Campus SOROCABA)Câmpus Sorocaba, 2016-01-29)
The goal of this study is to investigate the characteristics of the new data clustering approaches, carrying out a comparative study of clustering techniques that combine or select multiple solutions, analyzing these latest ...
Multi-objective clustering ensemble for gene expression data analysis
(ELSEVIER SCIENCE BV, 2009)
In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a ...
MILP-based clustering method for multi-objective optimization: Application to environmental problems
Multi-objective optimization (MOO) has recently emerged as a useful technique in environmental engineering. One major limitation of this approach is that its computational burden grows rapidly with the number of environmental ...
A computational multi-objective optimization method to improve energy efficiency and thermal comfort in dwellings
(Elsevier Science Sa, 2017-11)
In the last years, multi-objective optimization techniques became into one of the main challenges of the building energy efficiency area. The objective of this paper is to develop and validate a computational code for ...
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems
Recently, multi- and many-objective meta-heuristic algorithms have received considerable attention due to their capability to solve optimization problems that require more than one fitness function. This paper presents a ...
Partitions selection strategy for set of clustering solutions
(ELSEVIER SCIENCE BV, 2010)
Clustering is a difficult task: there is no single cluster definition and the data can have more than one underlying structure. Pareto-based multi-objective genetic algorithms (e.g., MOCK Multi-Objective Clustering with ...