Search results for "Aga"

showing 10 items of 4366 documents

Hybrid Particle Swarm Optimization With Genetic Algorithm to Train Artificial Neural Networks for Short-Term Load Forecasting

2019

This research proposes a new training algorithm for artificial neural networks (ANNs) to improve the short-term load forecasting (STLF) performance. The proposed algorithm overcomes the so-called training issue in ANNs, where it traps in local minima, by applying genetic algorithm operations in particle swarm optimization when it converges to local minima. The training ability of the hybridized training algorithm is evaluated using load data gathered by Electricity Generating Authority of Thailand. The ANN is trained using the new training algorithm with one-year data to forecast equal 48 periods of each day in 2013. During the testing phase, a mean absolute percentage error (MAPE) is used …

Artificial neural networkComputer sciencebusiness.industry020209 energyLoad forecastingTraining (meteorology)Particle swarm optimization02 engineering and technologyBackpropagationComputer Science ApplicationsTerm (time)Computational Theory and MathematicsArtificial IntelligenceGenetic algorithm0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessInternational Journal of Swarm Intelligence Research
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Tabu and Scatter Search for Artificial Neural Networks

2003

In this paper we address the problem of training multilayer feed-forward neural networks. These networks have been widely used for both prediction and classification in many different areas. Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been applied to solve this problem. This paper presents a new training algorithm based on the tabu search methodology that incorporates elements for search intensification and diversification by utilizing strategic designs where other previous approaches resort to randomization. Our method considers context and search information, as it is provided by th…

Artificial neural networkComputer sciencebusiness.industryContext (language use)Machine learningcomputer.software_genreBackpropagationTabu searchPartial derivativeArtificial intelligencebusinessMetaheuristicGlobal optimizationcomputerSelection (genetic algorithm)
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Daily Peak Temperature Forecasting with Elman Neural Networks

2005

This work presents a forecaster based on an Elman artificial neural network trained with resilient backpropagation algorithm for predicting the daily peak temperatures one day ahead. The available time series was recorded at Petrosino (TP), in the west coast of Sicily, Italy and it is composed by temperature (min and max values), the humidity (min and max values) and the rainfall value between January 1st, 1995 and May 14th, 2003. Performances and reliabilities of the proposed model were evaluated by a number of measures, comparing different neural models. Experimental results show very good prediction performances.

Artificial neural networkComputer sciencebusiness.industryLoad forecastingWeather forecastingHumiditycomputer.software_genreRpropBackpropagationStatisticsartificial neural networkTemperature forecastingPrecipitationWest coastArtificial intelligencebusinesscomputer
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Connectionist models of face processing: A survey

1994

Abstract Connectionist models of face recognition, identification, and categorization have appeared recently in several disciplines, including psychology, computer science, and engineering. We present a review of these models with the goal of complementing a recent survey by Samal and Iyengar [Pattern Recognition25, 65–77 (1992)] of nonconnectionist approaches to the problem of the automatic face recognition. We concentrate on models that use linear autoassociative networks, nonlinear autoassociative (or compression) and/or heteroassociative backpropagation networks. One advantage of these models over some nonconnectionist approaches is that analyzable features emerge naturally from image-b…

Artificial neural networkbusiness.industryComputer scienceFeature selectionMachine learningcomputer.software_genreFacial recognition systemBackpropagationCategorizationConnectionismArtificial IntelligenceFace (geometry)Signal ProcessingPattern recognition (psychology)Computer Vision and Pattern RecognitionArtificial intelligencebusinesscomputerSoftwarePattern Recognition
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Two-level branch prediction using neural networks

2003

Dynamic branch prediction in high-performance processors is a specific instance of a general time series prediction problem that occurs in many areas of science. Most branch prediction research focuses on two-level adaptive branch prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other application areas and fields for novel solutions to the problem. In this paper, we examine the application of neural networks to dynamic branch prediction. We retain the first level history register of conventional two-level predictors and replace the second level PHT with a neural network. Two neural networks are considered: a learning vec…

Artificial neural networkbusiness.industryTime delay neural networkComputer scienceVector quantizationLearning vector quantisationBranch predictorMachine learningcomputer.software_genreBackpropagationApplication areasHardware and ArchitectureArtificial intelligenceHardware_CONTROLSTRUCTURESANDMICROPROGRAMMINGTime seriesbusinesscomputerSoftwareJournal of Systems Architecture
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Absolute kinematics of radio-source components in the complete S5 polar cap sample: IV. Proper motions of the radio cores over a decade and spectral …

2016

We have carried out a high-precision astrometric analysis of two very-long-baseline-interferometry (VLBI) epochs of observation of the 13 extragalactic radio sources in the complete S5 polar cap sample. The VLBI epochs span a time baseline of ten years and enable us to achieve precisions in the proper motions of the source cores up to a few micro-arcseconds per year. The observations were performed at 14.4 GHz and 43.1 GHz, and enable us to estimate the frequency core-shifts in a subset of sources, for which the spectral-index distributions can be computed. We study the source-position stability by analysing the changes in the relative positions of fiducial source points (the jet cores) ove…

AstrofísicaActive galactic nucleusAstrometriaAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesAstrophysics::Cosmology and Extragalactic AstrophysicsAstrophysicsKinematics01 natural sciencesStability (probability)Radio continuum: generalBinary black hole0103 physical sciencesVery-long-baseline interferometry010306 general physicsInstrumentation and Methods for Astrophysics (astro-ph.IM)010303 astronomy & astrophysicsAstrophysics::Galaxy AstrophysicsPhysicsJet (fluid)general [Radio continuum]general [BL Lacertae objects]Astrophysics::Instrumentation and Methods for AstrophysicsAstronomy and Astrophysicsgeneral [Quasars]BL Lacertae objects: generalAstrometryAstrometryAstrophysics - Astrophysics of GalaxiesQuasars: generalGravitational lensSpace and Planetary ScienceAstrophysics of Galaxies (astro-ph.GA)Techniques: interferometricinterferometric [Techniques]Astrophysics - Instrumentation and Methods for Astrophysics
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The gamma-ray emitting radio-loud narrow-line Seyfert 1 galaxy PKS 2004-447 I. The X-ray View

2015

As part of the TANAMI multiwavelength progam, we discuss new X-ray observations of the $\gamma$-ray and radio-loud Narrow Line Seyfert galaxy ($\gamma$-NLS1) PKS 2004-447. The active galaxy is a member of a small sample of radio-loud NLS1s detected in $\gamma$-rays by the Fermi Large Area Telescope. It is the radio-loudest and only southern-hemisphere source in this sample. We present results from our X-ray monitoring program comprised of Swift snapshot observations from 2012 through 2014 and two new X-ray observations with XMM-Newton in 2012. We analyze the X-ray spectrum and variability of this peculiar source using supplementary archival data from 2004 and 2011. The (0.5-10) keV spectrum…

AstrofísicaActive galactic nucleusAstronomyAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesRadio spectrumlaw.inventionTelescopeRelativistic beaminglaw0103 physical sciencesVery-long-baseline interferometryBlazar010303 astronomy & astrophysicsAstrophysics::Galaxy AstrophysicsPhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)010308 nuclear & particles physicsAstronomy and AstrophysicsMonitoring programAstrophysics - Astrophysics of GalaxiesGalaxySpace and Planetary ScienceAstrophysics of Galaxies (astro-ph.GA)AstronomiaComputingMethodologies_DOCUMENTANDTEXTPROCESSINGAstrophysics - High Energy Astrophysical Phenomena
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LeMMINGs III. The e-MERLIN legacy survey of the Palomar sample: exploring the origin of nuclear radio emission in active and inactive galaxies throug…

2021

Full list of authors: Baldi, R. D.; Williams, D. R. A.; Beswick, R. J.; McHardy, I.; Dullo, B. T.; Knapen, J. H.; Zanisi, L.; Argo, M. K.; Aalto, S.; Alberdi, A.; Baan, W. A.; Bendo, G. J.; Fenech, D. M.; Green, D. A.; Klöckner, H. -R.; Körding, E.; Maccarone, T. J.; Marcaide, J. M.; Mutie, I.; Panessa, F.; Pérez-Torres, M. A.; Romero-Cañizales, C.; Saikia, D. J.; Saikia, P.; Shankar, F.; Spencer, R. E.; Stevens, I. R.; Uttley, P.; Brinks, E.; Corbel, S.; Martí-Vidal, I.; Mundell, C. G.; Pahari, M.; Ward, M. J.

AstrofísicaActive galactic nucleusAstronomyAstrophysics::High Energy Astrophysical Phenomenanuclei [galaxies]jets [galaxies]Doubly ionized oxygenFOS: Physical sciencesAstrophysicsF500Astrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesRadio continuum: galaxiesLuminosityAstrophysical jetSubatomic Physics0103 physical sciencesAstronomy Astrophysics and CosmologyAstrophysics::Solar and Stellar AstrophysicsConnection (algebraic framework)010303 astronomy & astrophysicsAstrophysics::Galaxy AstrophysicsGalaxies: nucleiAstronomia ObservacionsHigh Energy Astrophysical Phenomena (astro-ph.HE)Physics[SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph]Galaxies: star formation010308 nuclear & particles physicsAstronomy and AstrophysicsGalaxies: activeAstrophysics - Astrophysics of Galaxiesgalaxies [radio continuum]Accretion (astrophysics)Galaxy[SDU]Sciences of the Universe [physics]Meteorology and Atmospheric SciencesSpace and Planetary ScienceGalaxies: jetsAstrophysics of Galaxies (astro-ph.GA)active [galaxies]Production (computer science)star formation [galaxies]Astrophysics - High Energy Astrophysical Phenomena
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Event Horizon Telescope observations of the jet launching and collimation in Centaurus A

2021

Full list of authors: Janssen, Michael; Falcke, Heino; Kadler, Matthias; Ros, Eduardo; Wielgus, Maciek; Akiyama, Kazunori; Baloković, Mislav; Blackburn, Lindy; Bouman, Katherine L.; Chael, Andrew; Chan, Chi-kwan; Chatterjee, Koushik; Davelaar, Jordy; Edwards, Philip G.; Fromm, Christian M.; Gómez, José L.; Goddi, Ciriaco; Issaoun, Sara; Johnson, Michael D.; Kim, Junhan; Koay, Jun Yi; Krichbaum, Thomas P.; Liu, Jun; Liuzzo, Elisabetta; Markoff, Sera; Markowitz, Alex; Marrone, Daniel P.; Mizuno, Yosuke; Müller, Cornelia; Ni, Chunchong; Pesce, Dominic W.; Ramakrishnan, Venkatessh; Roelofs, Freek; Rygl, Kazi L. J.; van Bemmel, Ilse; Event Horizon Telescope Collaboration.--This Open Access artic…

AstrofísicaActive galactic nucleusCosmology and Nongalactic Astrophysics (astro-ph.CO)010504 meteorology & atmospheric sciencesEvent horizonastro-ph.GAAstronomyAstrophysics::High Energy Astrophysical PhenomenaAstrophysics - astrophysics of galaxiesAstrophysics - cosmology and nongalactic astrophysicsCentaurus AFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesAstrophysics - high energy astrophysical phenomena0103 physical sciencesVery-long-baseline interferometry010303 astronomy & astrophysicsAstrophysics::Galaxy Astrophysics0105 earth and related environmental sciencesAstronomia ObservacionsEvent Horizon TelescopePhysicsastro-ph.HEHigh Energy Astrophysical Phenomena (astro-ph.HE)Supermassive black holeJet (fluid)Galactic CenterAstronomy and AstrophysicsAstrophysics of Galaxies (astro-ph.GA)astro-ph.CO
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Why Have Many of the Brightest Radio-loud Blazars Not Been Detected in Gamma-Rays by Fermi?

2015

We use the complete MOJAVE 1.5 Jy sample of active galactic nuclei (AGNs) to examine the gamma-ray detection statistics of the brightest radio-loud blazars in the northern sky. We find that 23% of these AGNs were not detected above 0.1 GeV by the Fermi-LAT during the four-year 3FGL catalog period partly because of an instrumental selection effect and partly due to their lower Doppler boosting factors. Blazars with synchrotron peaks in their spectral energy distributions located below 10^(13.4) Hz also tend to have high-energy peaks that lie below the 0.1 GeV threshold of the LAT, and are thus less likely to be detected by Fermi. The non-detected AGNs in the 1.5 Jy sample also have significa…

AstrofísicaActive galactic nucleusmedia_common.quotation_subjectAstrophysics::High Energy Astrophysical Phenomenajets [galaxies]AstrophysicsAstrophysics::Cosmology and Extragalactic Astrophysicsgeneral [gamma-ray burst]7. Clean energy01 natural scienceslaw.inventionsymbols.namesakelaw0103 physical sciencesBlazar010303 astronomy & astrophysicsAstrophysics::Galaxy Astrophysicsmedia_commonPhysicsgeneral [quasars]010308 nuclear & particles physicsScatteringSpectral densityAstronomy and Astrophysicsgalaxies [radio continuum]Synchrotron13. Climate actionSpace and Planetary ScienceSkyactive [galaxies]AstronomiasymbolsDoppler effectFermi Gamma-ray Space Telescope
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