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» A framework for the description of evolutionary algorithms
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GECCO
2004
Springer
108views Optimization» more  GECCO 2004»
14 years 26 days ago
Simple Population Replacement Strategies for a Steady-State Multi-objective Evolutionary Algorithm
This paper explores some simple evolutionary strategies for an elitist, steady-state Pareto-based multi-objective evolutionary algorithm. The experimental framework is based on the...
Christine L. Mumford
BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...
Suzanne Matthews, Tiffani L. Williams
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 26 days ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia
CEC
2007
IEEE
13 years 9 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
GPEM
2010
134views more  GPEM 2010»
13 years 6 months ago
An ensemble-based evolutionary framework for coping with distributed intrusion detection
A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic p...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...