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» Short Term Unit-Commitment Using Genetic Algorithms
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KBSE
2007
IEEE
14 years 2 months ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
14 years 2 months ago
A systemic computation platform for the modelling and analysis of processes with natural characteristics
Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1]...
Erwan Le Martelot, Peter J. Bentley, R. Beau Lotto
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 9 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
KDD
2006
ACM
157views Data Mining» more  KDD 2006»
14 years 8 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen