Results 221 to 230 of about 228,099 (265)
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Vendor selection using genetic algorithm
The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012Selecting the right vendor is a complex business decision due to a huge number of competing vendors with a large number of complex criteria. The organization will suffer in the long run if vendors are not chosen wisely. Under multi criteria decision making, an algorithm, named VSFI, based on fuzzy clustering was proposed to select the most optimal ...
Shaila Sharmeen +4 more
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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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Genetic algorithms as a strategy for feature selection
Journal of Chemometrics, 1992AbstractGenetic algorithms have been created as an optimization strategy to be used especially when complex response surfaces do not allow the use of better‐known methods (simplex, experimental design techniques, etc.). This paper shows that these algorithms, conveniently modified, can also be a valuable tool in solving the feature selection problem ...
LEARDI, RICCARDO +2 more
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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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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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Feature subset selection using a genetic algorithm
IEEE Intelligent Systems, 1998Practical pattern-classification and knowledge-discovery problems require the selection of a subset of attributes or features to represent the patterns to be classified. The authors' approach uses a genetic algorithm to select such subsets, achieving multicriteria optimization in terms of generalization accuracy and costs associated with the features.
Jihoon Yang, Vasant G. Honavar
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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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