Search results for "evolutionary computation"

showing 10 items of 113 documents

An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GA

2015

In this paper, we describe an interactive evolutionary algorithm called Interactive WASF-GA to solve multiobjective optimization problems. This algorithm is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In Interactive WASF-GA, a decision maker (DM) provides preference information at each iteration simple as a reference point consisting of desirable objective function values and the number of solutions to be compared. Using this information, the desired number of solutions are generated to represent the region of interest of the Pareto optimal front associated to the reference point given. Interactive WASF-GA implies a much lower computational…

Mathematical optimizationOptimization problemMultiobjective programmingComputer scienceEvolutionary algorithmReference point approachInteractive evolutionary computationPareto optimal solutionsEvolutionary algorithmsPreference (economics)AlgorithmMulti-objective optimizationInteractive methods
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Agents Displacement in Arbitrary Geometrical Spaces: An Evolutionary Computation based Approach

2015

In many different social contexts, communication allows a collective intelligence to emerge. However, a correct way of exchanging information usually requires determined topological configurations of the agents involved in the process. Such a configuration should take into account several parameters, e.g. agents positioning, their proximity and time efficiency of communication. Our aim is to present an algorithm, based on evolutionary programming, which optimizes agents placement on arbitrarily shaped areas. In order to show its ability to deal with arbitrary bi-dimensional topologies, this algorithm has been tested on a set of differently shaped areas that present concavities, convexities …

OptimizationMathematical optimizationTheoretical computer scienceAgent ModelingSettore INF/01 - InformaticaComputer scienceTime efficiencyCollective intelligenceProcess (computing)Settore M-FIL/02 - Logica E Filosofia Della ScienzaObject (computer science)Network topologyDisplacement (vector)Agent-based Modeling OptimizationEvolutionary ComputationSet (psychology)Agent Modeling Optimization Evolutionary ComputationEvolutionary programming
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Evolutionary Algorithms and Metaheuristics : Applications in Engineering Design and Optimization

2018

Article SubjectComputer scienceoptimisationGeneral MathematicsEvolutionary algorithmevoluutiolaskenta02 engineering and technologytekoälyalgorithms01 natural sciences010305 fluids & plasmas0203 mechanical engineeringoptimointi0103 physical sciencesalgoritmitMetaheuristicta113business.industrylcsh:Mathematicsta111General Engineeringlcsh:QA1-939artificial intelligence020303 mechanical engineering & transportslcsh:TA1-2040evolutionary computationArtificial intelligenceEngineering design processbusinesslcsh:Engineering (General). Civil engineering (General)
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Self-organized modularization in evolutionary algorithms.

2005

The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenber…

Modularity (networks)education.field_of_studyTheoretical computer scienceComputer sciencebusiness.industryPopulationEvolutionary algorithmVariation (game tree)Modular designModels TheoreticalBiological EvolutionEvolutionary computationField (computer science)Computational MathematicsRange (mathematics)MutationArtificial intelligencebusinesseducationAlgorithmsEvolutionary computation
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An interactive evolutionary approach for content based image retrieval

2009

Content Based Image Retrieval (CBIR) systems aim to provide a means to find pictures in large repositories without using any other information except its contents usually as low-level descriptors. Since these descriptors do not exactly match the high level semantics of the image, assessing perceptual similarity between two pictures using only their feature vectors is not a trivial task. In fact, the ability of a system to induce high level semantic concepts from the feature vector of an image is one of the aspects which most influences its performance. This paper describes a CBIR algorithm which combines relevance feedback, evolutionary computation concepts and ad-hoc strategies in an attem…

Information retrievalbusiness.industryComputer scienceFeature vectorFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRelevance feedbackPattern recognitionContent-based image retrievalSemanticsEvolutionary computationHistogramVisual WordArtificial intelligencebusinessImage retrieval2009 IEEE International Conference on Systems, Man and Cybernetics
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Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder

2020

This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed c…

0209 industrial biotechnologyAdaptive controlFluid PowerComputer sciencemotion controlComputer Science::Neural and Evolutionary Computationhydraulicsdifferential cylinder02 engineering and technologyAdaptiv reguleringadaptive controllcsh:TechnologyRoot mean squarelcsh:Chemistry020901 industrial engineering & automationControl theoryConvergence (routing)feedforwardCylinderGeneral Materials ScienceVDP::Andre maskinfag: 579Instrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processeslcsh:TProcess Chemistry and TechnologyGeneral EngineeringFeed forwardVDP::Other machinery sciences: 579021001 nanoscience & nanotechnologyMotion controllcsh:QC1-999BevegelsesstyringComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Hydraulikk0210 nano-technologyReduction (mathematics)lcsh:Engineering (General). Civil engineering (General)lcsh:PhysicsApplied Sciences
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GRASP & evolutionary path relinking for medical image registration based on point matching

2010

Image registration is a very active research area in computer vision. Image registration methods, aim to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation can be inferred by means of numerical methods. In this paper, we tackle the medical image registration problem adapting a new advanced hybrid metaheuristic composed by the GRASP and the evolutionary path relinking algorithms, called G&EvPR. The experiments conducted in this work have shown the good performance of G&EvPR compared to similar a…

Matching (statistics)business.industryGRASPComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationPoint set registrationEvolutionary computationElectronic mailComputer visionArtificial intelligencebusinessMetaheuristicGreedy randomized adaptive search procedureMathematicsIEEE Congress on Evolutionary Computation
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Synchronised gravitational atoms from mergers of bosonic stars

2020

If ultralight bosonic fields exist in Nature as dark matter, superradiance spins down rotating black holes (BHs), dynamically endowing them with equilibrium bosonic clouds, here dubbed synchronised gravitational atoms (SGAs). The self-gravity of these same fields, on the other hand, can lump them into (scalar or vector) horizonless solitons known as bosonic stars (BSs). We show that the dynamics of BSs yields a new channel forming SGAs. We study BS binaries that merge to form spinning BHs. After horizon formation, the BH spins up by accreting the bosonic field, but a remnant lingers around the horizon. If just enough angular momentum is present, the BH spin up stalls precisely as the remnan…

PhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)High Energy Physics - TheoryAngular momentumSpins010308 nuclear & particles physicsHorizonAstrophysics::High Energy Astrophysical PhenomenaDark matterComputer Science::Neural and Evolutionary ComputationFOS: Physical sciencesGeneral Relativity and Quantum Cosmology (gr-qc)Quantum number01 natural sciences7. Clean energyAccretion (astrophysics)General Relativity and Quantum CosmologyGravitationHigh Energy Physics - Theory (hep-th)Quantum mechanics0103 physical sciencesBosonic field010306 general physicsAstrophysics - High Energy Astrophysical Phenomena
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Are Neural Networks Imitations of Mind?

2015

Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.

Structure (mathematical logic)Artificial neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryComputationComputer Science::Neural and Evolutionary ComputationAcknowledgementShort-term memoryRecurrent networkBrainFeed-forward networkSettore M-FIL/02 - Logica E Filosofia Della ScienzaPerceptroncomputer.software_genreMindSimilitudeHopfield networkArtificial intelligenceData miningbusinesscomputer
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The electron affinity of astatine

2020

One of the most important properties influencing the chemical behavior of an element is the electron affinity (EA). Among the remaining elements with unknown EA is astatine, where one of its isotopes, 211At, is remarkably well suited for targeted radionuclide therapy of cancer. With the At− anion being involved in many aspects of current astatine labeling protocols, the knowledge of the electron affinity of this element is of prime importance. Here we report the measured value of the EA of astatine to be 2.41578(7) eV. This result is compared to state-of-the-art relativistic quantum mechanical calculations that incorporate both the Breit and the quantum electrodynamics (QED) corrections and…

Atomic Physics (physics.atom-ph)ENERGIESGeneral Physics and AstronomyElectron01 natural sciences7. Clean energyPhysics - Atomic PhysicsElectronegativityastatiinielectron affinityPhysics::Atomic Physicslcsh:SciencePhysicsMultidisciplinary010304 chemical physicsIsotopeQELECTRONEGATIVITYMultidisciplinary SciencesHalogenScience & Technology - Other Topicsddc:500Atomic physicsBASIS-SET CONVERGENCE[CHIM.RADIO]Chemical Sciences/RadiochemistryRadioactive decayChemical physicsAstrophysics::High Energy Astrophysical PhenomenaScienceComputer Science::Neural and Evolutionary ComputationOther Fields of PhysicsPOTENTIALSFOS: Physical scienceschemistry.chemical_elementphysics.atom-phGeneral Biochemistry Genetics and Molecular BiologyArticleIonElectron affinity0103 physical sciences[CHIM]Chemical Sciences010306 general physicsAstatineDETECTORScience & TechnologySTABILITYRadiochemistry500General Chemistrychemistrylcsh:Qastatine
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