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PR
1998
86views more  PR 1998»
15 years 6 months ago
Optimizing the cost matrix for approximate string matching using genetic algorithms
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
Marc Parizeau, Nadia Ghazzali, Jean-Françoi...
TNN
1998
76views more  TNN 1998»
15 years 6 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
JDCTA
2010
186views more  JDCTA 2010»
15 years 1 months ago
A Positioning Method in Wireless Sensor Networks Using Genetic Algorithms
The recent area of Wireless Sensor Networks (WSNs) has brought new challenges to developers of net-work protocols. Energy consumption and network coverage are two important challe...
Mojtaba Romoozi, Hossein Ebrahimpour-Komleh
PAMI
2006
134views more  PAMI 2006»
15 years 6 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Michael Laszlo, Sumitra Mukherjee
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
15 years 10 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon