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GECCO
2005
Springer
177views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving next generation signal compression and reconstruction transforms via genetic algorithms
Ongoing research has established a new methodology for using genetic algorithms [2] to evolve forward and inverse transforms that significantly reduce quantization error in recons...
Frank W. Moore, Patrick Marshall
GECCO
2004
Springer
123views Optimization» more  GECCO 2004»
14 years 1 months ago
A Hybrid Genetic Approach for Circuit Bipartitioning
We propose a hybrid genetic algorithm for partitioning a VLSI circuit graph into two disjoint graphs of minimum cut size. The algorithm includes a local optimization heuristic whic...
Jong-Pil Kim, Yong-Hyuk Kim, Byung Ro Moon
GECCO
1999
Springer
14 years 6 days ago
Large Populations Are Not Always The Best Choice In Genetic Programming
In genetic programming a general consensus is that the population should be as large as practically possible or sensible. In this paper we examine a batch of problems of combinato...
Matthias Fuchs
EUROGP
1998
Springer
14 years 5 days ago
Speech Sound Discrimination with Genetic Programming
The question that we investigate in this paper is, whether it is possible for Genetic Programming to extract certain regularities from raw time series data of human speech. We exam...
Markus Conrads, Peter Nordin, Wolfgang Banzhaf
GECCO
2006
Springer
447views Optimization» more  GECCO 2006»
13 years 11 months ago
Candlestick stock analysis with genetic algorithms
Candlestick analysis, a form of stock market technical analysis, is well suited for use with a genetic search algorithm. This paper explores an implementation of marrying these tw...
Peter Belford