CP
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. We study the problem of maximizing the amount of stochastic diffusion in a network by acquiring nodes within a certain limited budget. We use a Sample Average Approximati...
CP
2010
Springer
13 years 9 months ago
2010
Springer
Coupling constraints and ordinary differential equations has numerous applications. This paper shows how to introduce constraints involving ordinary differential equations into the...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a mo...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
Abstract-- In this paper, a segmentation technique of multispectral magnetic resonance image of the brain using a new differential evolution based crisp clustering is proposed. Rea...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
Abstract-- We present a case study demonstrating that using the REVAC parameter tuning method we can greatly improve the `world champion' EA (the winner of the CEC2005 competi...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
This paper describes and experimentally evaluates the viability of the (
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
Abstract-- In this paper we present a new version of a GPbased financial forecasting tool called EDDIE. The novelty of this new version (EDDIE 8), is its enlarged search space, whe...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
In this paper we present self-adaptive differential evolution algorithm jDElsgo on large scale global optimization. The experimental results obtained by our algorithm on benchmark ...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
This paper focuses on the application of a new ACO-based automatic programming algorithm to the classification task of data mining. This new model, called GBAP algorithm, is based ...
CEC
2010
IEEE
13 years 9 months ago
2010
IEEE
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...