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» A Graphical Model for Evolutionary Optimization
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
15 years 27 days ago
A hybrid method for tuning neural network for time series forecasting
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
Aranildo Rodrigues Lima Junior, Tiago Alessandro E...
GECCO
2004
Springer
179views Optimization» more  GECCO 2004»
15 years 5 months ago
An Evolutionary Meta Hierarchical Scheduler for the Linux Operating System
Abstract. The need for supporting CSCW applications with heterogeneous and varying user requirements calls for adaptive and reconfigurable schedulers accommodating a mixture of re...
Horst Wedde, Muddassar Farooq, Mario Lischka
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 5 months ago
Evolutionary computation and the c-value paradox
The C-value Paradox is the name given in biology to the wide variance in and often very large amount of DNA in eukaryotic genomes and the poor correlation between DNA length and p...
Sean Luke
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 5 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
SEAL
2010
Springer
14 years 9 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...