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» Terrain generation using genetic algorithms
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TNN
1998
76views more  TNN 1998»
13 years 7 months ago
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-d
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
Rajeev Kumar, Peter Rockett
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 23 days ago
Evolving Consensus Sequence for Multiple Sequence Alignment with a Genetic Algorithm
In this paper we present an approach that evolves the consensus sequence [25] for multiple sequence alignment (MSA) with genetic algorithm (GA). We have developed an encoding schem...
Conrad Shyu, James A. Foster
ICTAI
2000
IEEE
13 years 12 months ago
Constrained genetic algorithms and their applications in nonlinear constrained optimization
This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not ne...
Benjamin W. Wah, Yixin Chen
ICDAR
2003
IEEE
14 years 25 days ago
Feature Selection for Ensembles: A Hierarchical Multi-Objective Genetic Algorithm Approach
Feature selection for ensembles has shown to be an effective strategy for ensemble creation. In this paper we present an ensemble feature selection approach based on a hierarchica...
Luiz E. Soares de Oliveira, Robert Sabourin, Fl&aa...
PPSN
1994
Springer
13 years 11 months ago
Convergence Models of Genetic Algorithm Selection Schemes
We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes. The models predict the proportion of optimal a...
Dirk Thierens, David E. Goldberg