Tesi proiektu honetako xede nagusia, eguzki-sistema grabitazionalaren N gorputzekoproblemen zenbakizko epe luzeko simulaziorako algoritmoak garatzea da. Gaur egun,era horretako simulaziotarako hainbat zenbakizko metodo ...

In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances ...

Bertsobot: Robot-Portaerak Gizaki-Robot Arteko Komunikazio eta ElkarrekintzanBertsotan aritzeko gaitasuna erakutsiko duen robot autonomoa garatzeada gure ikerketa-lanaren helburu behinena. Bere egitekoa, bertsoa ...

The increasing ability to gather, store and process health care information, through the electronic health records and improved communication methods opens the door for new applications intended to improve health care in ...

A classical supervised classification task tries to predict a single class variable based on a data set composed of a set of labeled examples. However, in many real domains more than one variable could be considered as a ...

This paper describes MATEDA-2.0, a suite of programs in Matlab for estimation of distribution algorithms. The package allows the optimization of single and multi-objective problems with estimation of distribution algorithms ...

The successful application of estimation of distribution algorithms (EDAs) to solve different kinds of problems has reinforced their candidature as promising black-box optimization tools. However, their internal behavior is ...

In the machine learning field the performance of a classifier is usually measured in terms of prediction error. In most real-world problems, the error cannot be exactly calculated and it must be estimated. Therefore, it’s ...

This paper presents an algorithm for the automatic selection of a minimal subset of tagging single nucleotide polymorphisms (SNPs) using an estimation of distribution algorithm (EDA). The EDA stochastically searches the ...

Haplotype data is especially important in the study of complex diseases since it contains more information than genotype data. However, obtaining haplotype data is technically difficult and expensive. Computational methods ...