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» Timetable Scheduling Using Particle Swarm Optimization
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PPSN
2004
Springer
14 years 27 days ago
Optimization via Parameter Mapping with Genetic Programming
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...
João Carlos Figueira Pujol, Riccardo Poli
ISNN
2005
Springer
14 years 1 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang
ISNN
2004
Springer
14 years 27 days ago
Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithm
A flexible neural network (FNN) is a multilayer feedforward neural network with the characteristics of: (1) overlayer connections; (2) variable activation functions for different...
Yuehui Chen, Bo Yang, Jiwen Dong
CEC
2010
IEEE
13 years 5 months ago
Comparison of GA and PSO performance in parameter estimation of microbial growth models: A case-study using experimental data
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...
Dulce Calcada, Agostinho Rosa, Luis C. Duarte, Vit...
IJCAI
1989
13 years 8 months ago
Constraint Satisfiability Algorithms for Interactive Student Scheduling
A constraint satisfiability problem consists of a set of variables, their associated domains (i.e., the set of values the variable can take) and a set of constraints on these vari...
Ronen Feldman, Martin Charles Golumbic