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Artículo
BIGOWL: Knowledge centered Big Data analytics
(Elsevier, 2019)
Knowledge extraction and incorporation is currently considered to be beneficial for efficient Big Data an- alytics. Knowledge can take part in workflow design, constraint definition, parameter selection and con- figuration, ...
Ponencia
Automatic Configuration of NSGA-II with jMetal and irace
(ACM Digital Library, 2019)
jMetal is a Java-based framework for multi-objective optimization with metaheuristics providing, among other features, a wide set of algorithms that are representative of the state-of-the-art. Although it has become a ...
Ponencia
Algoritmos Basados en Cúmulos de Partículas para el Análisis de Microarrays de ADN
([Los editores], 2007)
Artículo
A multi-objective interactive dynamic particle swarm optimizer
(Springer, 2020)
Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized simulta-neously. When the objectives change somehow with time, the problems become dynamic, and if the ...
Ponencia
ROS: Servicio de Optimización Remota
(SISTEDES: Ingeniería de Software y las Tecnologías de Desarrollo de Software, 2006)
En este artículo se describe ROS, un Servicio de Optimización Remota. ROS permite a sus usuarios tener acceso a un conjunto de algoritmos modernos de optimizaci ón, situados en repositorios con recursos hardware y software ...
Ponencia
Gene Selection in Cancer Classification using PSO/SVM and GA/SVM Hybrid Algorithms
(IEEE Computer Society, 2007)
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high dimensional Microarray Data. ...
Artículo
jMetalSP: A framework for dynamic multi-objective big data optimization
(Elsevier, 2018)
Multi-objective metaheuristics have become popular techniques for dealing with complex optimization problems composed of a number of conflicting functions. Nowadays, we are in the Big Data era, so metaheuristics must be ...
Artículo
Optimizing ligand conformations in flexible protein targets: amulti-objective strategy
(Springer, 2020)
Finding the orientation of a ligand (small molecule) with the lowest binding energy to the macromolecule (receptor) is a complex optimization problem, commonly called ligand–protein docking. This problem has been usually ...
Ponencia
Island Based Distributed Differential Evolution: An Experimental Study on Hybrid Testbeds
(IEEE Computer Society, 2008)
This paper presents a new distributed Differential Evolution (dDE) algorithm and evaluates it according to the standard procedure set in the special session of continuous optimization of CEC’05. We statistically validate ...
Artículo
Qom—A New Hydrologic Prediction Model Enhanced with Multi-Objective Optimization
(MDPI, 2019)
The efficient calibration of hydrologic models allows experts to evaluate past events in river basins, as well as to describe new scenarios and predict possible future floodings. A difficulty in this context is the need ...