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Genetic Algorithm Guided Selection: Variable Selection and Subset Selection
Journal of Chemical Information and Computer Sciences, 2002A novel Genetic Algorithm guided Selection method, GAS, has been described. The method utilizes a simple encoding scheme which can represent both compounds and variables used to construct a QSAR/QSPR model. A genetic algorithm is then utilized to simultaneously optimize the encoded variables that include both descriptors and compound subsets.
Sung Jin Cho, Mark A. Hermsmeier
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Genetic Programming with a Genetic Algorithm for Feature Construction and Selection
Genetic Programming and Evolvable Machines, 2005The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is classified using the C4.5 decision tree learning algorithm.
Matthew Goble Smith, Larry Bull
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Selective breeding in a multiobjective genetic algorithm
1998This paper describes an investigation of the efficacy of various elitist selection strategies in a multiobjective Genetic Algorithm implementation, with parents being selected both from the current population and from the archive record of nondominated solutions encountered during search.
Geoffrey T. Parks, I. Miller
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Selection Analysis in Genetic Algorithms
1998This paper describes a formal framework for the analysis of genetic algorithms. The model is based on the idea that over the space of populations an equivalence relation can be defined, as well as a metric on the space of equivalence classes induced by this relation.
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Automated Operator Selection on Genetic Algorithms
2005Genetic Algorithms (GAs) have proven to be a useful means of finding optimal or near optimal solutions to hard problems that are difficult to solve by other means. However, determining which crossover and mutation operator is best to use for a specific problem can be a complex task requiring much trial and error. Furthermore, different operators may be
Fredrik G. Hilding, Koren Ward
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A genetic algorithm for feature selection in gait analysis
2016 IEEE Congress on Evolutionary Computation (CEC), 2016This paper deals with the opportunity of extracting useful information from medical data retrieved directly from a stereophotogrammetric system applied to gait analysis, which aims at controlling movements of patients affected by neurological diseases. The proposed approach is intended to a feature selection procedure as an optimization strategy based ...
ALTILIO, ROSA +4 more
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GrC model in Genetic Algorithm: Artificial Selection Algorithm
2008 IEEE International Conference on Granular Computing, 2008Genetic Algorithm (GA), a programming technique that mimics natural evolution as a problem-solving strategy, has become popular since its appearance. It keeps the properties similar to natural selection systems. Many improved GAs has been proposed, however, natural selection essence is not changed.
Zehua Chen 0001 +3 more
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Biologically Inspired Parent Selection in Genetic Algorithms
Annals of Operations Research, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zvi Drezner, Taly Dawn Drezner
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Formal models of selection in genetic algorithms
1994In this paper three formal models of selection operators (two known from the literature and one newly porposed) for genetic algorithms, used to learn structured concepts descriptions containing small disjuncts, are presented. The evolution of a population, according to these operators, with a generation gap equal to or less than one, is investigated in
Attilio Giordana +2 more
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Entropy-Boltzmann selection in the genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2003A new selection method, entropy-Boltzmann selection, for genetic algorithms (GAs) is proposed. This selection method is based on entropy and importance sampling methods in Monte Carlo simulation. It naturally leads to adaptive fitness in which the fitness function does not stay fixed but varies with the environment.
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