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» An evolutionary method for complex-process optimization
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CEC
2009
IEEE
15 years 7 months ago
Evolutionary image segmentation based on multiobjective clustering
— In the fields of image processing and recognition, image segmentation is an important basic technique in which an image is partitioned into multiple regions (sets of pixels). ...
Shinichi Shirakawa, Tomoharu Nagao
106
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ICML
2003
IEEE
15 years 5 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
GECCO
2005
Springer
116views Optimization» more  GECCO 2005»
15 years 6 months ago
An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization
We focus on the handling of overlapping solutions in evolutionary multiobjective optimization (EMO) algorithms. First we show that there exist a large number of overlapping soluti...
Hisao Ishibuchi, Kaname Narukawa, Yusuke Nojima
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
15 years 6 months ago
Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization
In the design of evolutionary multiobjective optimization (EMO) algorithms, it is important to strike a balance between diversity and convergence. Traditional mask-based crossover...
Hisao Ishibuchi, Yusuke Nojima, Noritaka Tsukamoto...
NC
1998
101views Neural Networks» more  NC 1998»
15 years 1 months ago
Evolutionary Optimized Tensor Product Bernstein Polynomials versus Backpropagation Networks
In this paper a new approach for approximation problems involving only few input and output parameters is presented and compared to traditional Backpropagation Neural Networks (BP...
Günther R. Raidl, Gabriele Kodydek