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SYNASC
2006
IEEE
95views Algorithms» more  SYNASC 2006»
14 years 1 months ago
Evolutionary Support Vector Regression Machines
Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
GECCO
2006
Springer
174views Optimization» more  GECCO 2006»
13 years 11 months ago
On the analysis of the (1+1) memetic algorithm
Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory...
Dirk Sudholt
GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
14 years 1 months ago
Exploiting gradient information in numerical multi--objective evolutionary optimization
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Peter A. N. Bosman, Edwin D. de Jong
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
14 years 1 months ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
EVOW
2009
Springer
14 years 2 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne