Listar1. Investigación por tema "Genetic algorithms"
Mostrando ítems 1-18 de 18
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A genetic algorithms-based approach for optimizing similarity aggregation in ontology matching
(Springer, 2013)[Abstract] Ontology matching consists of finding the semantic relations between different ontologies and is widely recognized as an essential process to achieve an adequate interoperability between people, systems or ... -
A point-based redesign algorithm for designing geometrically complex surfaces. A case study: Miralles's croissant paradox
(Jonh Wiley & Sons, 2020)[Abstract]: This study explores the use of point clouds for both representation and genetic morphogenesis of complex geometry. The accurate representation of existing objects of complex curved geometry, which are subsequently ... -
Approach of Genetic Algorithms With Grouping Into Species Optimized With Predator-Prey Method for Solving Multimodal Problems
(Springer, 2012)[Abstract] Over recent years, Genetic Algorithms have proven to be an appropriate tool for solving certain problems. However, it does not matter if the search space has several valid solutions, as their classic approach ... -
Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution
(World Scientific, 2015-04-06)[Abstract] Artificial Neuron–Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way ... -
Crushing analysis and multi-objective crashworthiness optimization of GFRP honeycomb-filled energy absorption devices
(Elsevier, 2014)[Abstract:] Fuel efficiency and occupant safety are two of the most important concerns in the automotive industry nowadays. Encouraged by the importance of this field of study, this research attempts an improvement in the ... -
Design of Reconfigurable Array Antennas With Minimum Variation of Active Impedances
(Institute of Electrical and Electronics Engineers, 2006-12)[Abstract] In this letter, the authors propose an optimization method based on the genetic algorithm (GA) to reconfigure a linear array of vertical half-wavelength dipole antennas to generate two patterns with minimum ... -
Evolutionary Computation and QSAR Research
(Bentham Science, 2013)[Abstract] The successful high throughput screening of molecule libraries for a specific biological property is one of the main improvements in drug discovery. The virtual molecular filtering and screening relies greatly ... -
Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity
(Springer, 2024)[Abstract]: Retinal vascular tortuosity is an excessive bending and twisting of the blood vessels in the retina that is associated with numerous health conditions. We propose a novel methodology for the automated assessment ... -
High performance genetic algorithm for land use planning
(Pergamon Press, 2013)[Abstract] This study uses genetic algorithms to formulate and develop land use plans. The restrictions to be imposed and the variables to be optimized are selected based on current local and national legal rules and ... -
Optimisation of Thin-Walled Hybrid Vertical Struts for Crashworthy Aircraft Designs
(Springer, 2020)[Abstract] This research concerns the crashworthiness enhancement of a model of a Boeing 737-200 fuselage section. Using a validated numerical specimen, four thin-walled crushable hybrid energy absorbers are added to the ... -
Optimizing parcel exchange among landowners: A soft alternative to land consolidation
(Elsevier, 2020-01)[Abstract]: For decades, public policy has favored the use of land consolidation to reduce the fragmentation of land ownership. Private actors, on the other hand, have focused on the purchase, rental and exchange of land ... -
Predicting vertical urban growth using genetic evolutionary algorithms in Tokyo’s minato ward
(American Society of Civil Engineers, 2018-03)[Abstract] This article explores the use of evolutionary genetic algorithms to predict scenarios of urban vertical growth in large urban centers. Tokyo’s Minato Ward is used as a case study because it has been one of the ... -
Self-tuning of disk input–output in operating systems
(Elsevier Inc., 2012-01)One of the most difficult and hard to learn tasks in computer system management is tuning the kernel parameters in order to get the maximum performance. Traditionally, this tuning has been set using either fixed configurations ... -
Texture classification of proteins using support vector machines and bio-inspired metaheuristics
(Springer, 2014-11-02)[Abstract] In this paper, a novel classification method of two-dimensional polyacrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for ... -
Use of a Genetic Algorithm to Optimize Wheel Profile Geometry
(Institution of Mechanical Engineers ; SAGE, 2007-07-01)[Abstract] Wear is a very important subject for Railway Administrations because it entails very important costs. So, it seems to be logical to develop a new methodology for designing wheel profiles in order to improve its ... -
Use of Multiple Astrocytic Configurations within an Artificial Neuro-Astrocytic Network
(MDPI AG, 2019-08-07)[Abstract] The artificial neural networks used in a multitude of fields are achieving good results. However, these systems are inspired in the vision of classical neuroscience where neurons are the only elements that process ... -
Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
(Inderscience, 2013)[Abstract] ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, fe w ... -
Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils
(Emerald, 2016-06)[Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ...