Results 21 to 30 of about 714,519 (262)
Feature selection using genetic algorithms and probabilistic neural networks [PDF]
, 2000 Selection of input variables is a key stage in building predictive models, and an important form of data mining. As exhaustive evaluation of potential input sets using full non-linear models is impractical, it is necessary to use simple fast-evaluating ...
Hunter, Andrew
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Flexible job shop scheduling using genetic algorithm and heuristic rules
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2016 Job shop scheduling with the availability of more than one machine to perform an operation, also known as the flexible job shop scheduling problem, is computationally NP-hard.
Parinya KAWEEGITBUNDIT, Toru EGUCHI
doaj +1 more source
Full model selection in the space of data mining operators [PDF]
, 2012 We propose a framework and a novel algorithm for the full model selection (FMS) problem. The proposed algorithm, combining both genetic algorithms (GA) and particle swarm optimization (PSO), is named GPS (which stands for GAPSO-FMS), in which a GA is ...
Mayo, Michael +2 more
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Rare-Event Sampling Analysis Uncovers the Fitness Landscape of the Genetic Code [PDF]
, 2022 The genetic code refers to a rule that maps 64 codons to 20 amino acids. Nearly all organisms, with few exceptions, share the same genetic code, the standard genetic code (SGC). While it remains unclear why this universal code has arisen and been maintained during evolution, it may have been preserved under selection pressure.
arxiv +1 more source
A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection [PDF]
, 2015 This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Multi-Label Correlation-based Feature Selection (LexGA-ML-CFS), which is an extension of the previous single-objective Genetic Algorithm for Multi-label Correlation-based ...
Freitas, Alex A., Jungjit, Suwimol
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Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function
Journal of Control Science and Engineering, 2022 To reduce the complexity and multiple constraints of logistics distribution routing problems, the author proposes an improved genetic algorithm, adaptive immune genetic algorithm (AIGA).
Hui Wen
doaj +1 more source
Subcontractor Selection using Genetic Algorithm
Procedia Engineering, 2015 AbstractIn the construction industry, subcontracting is a very common practice. Nowadays, most of the general contractors tend to sublet the large portions of construction works to subcontractors and they only act as construction management agencies. In other words, while subcontractors carry out the actual production work, general contractors organize
Barıs Kaplan +2 more
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Prototype Selection for Dissimilarity Representation by a Genetic Algorithm [PDF]
2010 20th International Conference on Pattern Recognition, 2010 Dissimilarities can be a powerful way to represent objects like strings, graphs and images for which it is difficult to find good features. The resulting dissimilarity space may be used to train any classifier appropriate for feature spaces. There is, however, a strong need for dimension reduction.
Plasencia-Calana Y. +3 more
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Improving Floating Search Feature Selection using Genetic Algorithm
Journal of ICT Research and Applications, 2017 Classification, a process for predicting the class of a given input data, is one of the most fundamental tasks in data mining. Classification performance is negatively affected by noisy data and therefore selecting features relevant to the problem is a ...
Kanyanut Homsapaya, Ohm Sornil
doaj +1 more source
Selection of attributes for modelling Bach chorales by a genetic algorithm [PDF]
, 1995 A genetic algorithm selected combinations of attributes for a machine learning system. The algorithm used 90 Bach chorale melodies to train models and randomly selected sets of 10 chorales for evaluation.
Hall, Mark A.
core +3 more sources