Search results for "Probability"

showing 10 items of 3417 documents

Contrasting probabilistic and anti-optimization approaches in an applied mechanics problem

2003

Probabilistic and non-probabilistic, anti-optimization analyses of uncertainty are contrasted in this study. Specifically, the comparison of these two competing approaches is conducted for an uniform column, with initial geometric imperfection, subjected to an impact axial load. The reliability of the column is derived for the cases when the initial imperfections posses either (a) uniform probability density, (b) truncated exponential density or (c) generic truncated probability density. The problem is also analyzed in the context of an interval analysis. It is shown that in, the most important near-unity reliability range these two approaches tend to each other. Since the interval analysis…

Applied MathematicsMechanical EngineeringProbabilistic logicProbability density functionContext (language use)Condensed Matter PhysicsColumn (database)Interval arithmeticMechanics of MaterialsModeling and SimulationStatisticsRange (statistics)Axial loadApplied mathematicsGeneral Materials ScienceReliability (statistics)MathematicsInternational Journal of Solids and Structures
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Itô calculus extended to systems driven by -stable Lévy white noises (a novel clip on the tails of Lévy motion)

2007

Abstract The paper deals with probabilistic characterization of the response of non-linear systems under α -stable Levy white noise input. It is shown that, by properly selecting a clip in the probability density function of the input, the moments of the increments of Levy motion process remain all of the same order ( d t ) , like the increments of the Compound Poisson process. It follows that the Ito calculus extended to Poissonian input, may also be used for α -stable Levy white noise input processes. It is also shown that, when the clip on the tails of the probability of the increments of the Levy motion approaches to infinity, the Einstein–Smoluchowsky equation is restored. Once these c…

Applied MathematicsMechanical Engineeringmedia_common.quotation_subjectMonte Carlo methodMathematical analysisTruncated Lévy motionProbabilistic logicProbability density functionItô calculuWhite noiseExtension (predicate logic)InfinityLévy processMechanics of Materialsα-Stable processeCompound Poisson processEinstein-Smoluchowsky equationMathematicsmedia_commonInternational Journal of Non-Linear Mechanics
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An innovative approach to manage uncertainties and stock diversity in the EPBD cost-optimal methodology

2018

The EU Energy Performance of Buildings Directive (EPBD) 2010/31/EU is a step in the right direction to promote near zero energy buildings (NZEB) in a step-wise manner, starting with minimum energy performance and cost optimal thresholds for “reference buildings” (RBs) for each category. Nevertheless, a standard method for defining RBs does not exist, which led to a great divergence between MS in the level of detail used to define RBs for the EPBD cost-optimal analysis. Such lack of harmonisation between MS is further evident given the resulting large discrepancies in energy performance indicators even between countries having similar climate. Furthermore, discrepancies of 30% or higher betw…

Architecture and energy conservationZero-energy buildingSettore ING-IND/11 - Fisica Tecnica AmbientaleOperations researchStock modelling EPBD cost-optimal method Bayesian calibration reference zonesEnergy performance indicatorsbusiness.industryComputer scienceBayesian probabilityEnergy performanceEngineering MultidisciplinaryMühendislik Ortak DisiplinlerBuildings -- Energy conservationDirectiveSoftwareStock modellingEPBD cost-optimal methodBayesian calibrationreference zonesBuildings -- Energy conservation -- European Union countriesSustainable buildings -- Design and construction -- StandardsbusinessZoningBuildings -- Thermal propertiesStock (geology)
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Stability of impulsive differential systems

2013

The asymptotic phase property and reduction principle for stability of a trivial solution is generalized to the case of the noninvertible impulsive differential equations in Banach spaces whose linear parts split into two parts and satisfy the condition of separation.

Article SubjectDifferential equationlcsh:MathematicsApplied MathematicsMathematical analysisPhase (waves)Banach spacelcsh:QA1-939Differential systemsStability (probability)Trivial solution:MATHEMATICS::Applied mathematics [Research Subject Categories]Reduction (mathematics)AnalysisMathematics
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Delay-Probability-Distribution-Dependent FIR Filtering Design with Envelope Constraints

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/930927 Open Access This paper studies the problem of H∞ finite-impulse response (FIR) filtering design of time-delay system. The time-delay considered here is time-varying meanwhile with a certain stochastic characteristic, and the probability of delay distribution is assumed to be known. Furthermore, the requirement of pulse-shape is also considered in filter design. Employing the information about the size and probability distribution of delay, a delay-probability-distribution-dependent criterion is proposed for the filtering error syst…

Article SubjectDistribution (number theory)lcsh:MathematicsGeneral MathematicsGeneral EngineeringLinear matrixlcsh:QA1-939Set (abstract data type)Filter designlcsh:TA1-2040Control theoryProbability distributionVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Analyse: 411lcsh:Engineering (General). Civil engineering (General)Envelope (mathematics)MathematicsMathematical Problems in Engineering
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Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model

2018

[EN] We present a Bayesian stochastic susceptible-exposed-infectious-recovered model in discrete time to understand chickenpox transmission in the Valencian Community, Spain. During the last decades, different strategies have been introduced in the routine immunization program in order to reduce the impact of this disease, which remains a public health's great concern. Under this scenario, a model capable of explaining closely the dynamics of chickenpox under the different vaccination strategies is of utter importance to assess their effectiveness. The proposed model takes into account both heterogeneous mixing of individuals in the population and the inherent stochasticity in the transmiss…

Article SubjectGeneral Computer ScienceComputer scienceComputationBayesian probabilityPosterior probabilityPopulation01 natural scienceslcsh:QA75.5-76.95010305 fluids & plasmas010104 statistics & probabilityMixing (mathematics)0103 physical sciencesmedicineEconometrics0101 mathematicseducationeducation.field_of_studyMultidisciplinaryChickenpoxPrediction intervalmedicine.diseaseVaccinationDiscrete time and continuous timePosterior predictive distributionlcsh:Electronic computers. Computer scienceMATEMATICA APLICADA
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Refitting Solutions Promoted by $$\ell _{12}$$ Sparse Analysis Regularizations with Block Penalties

2019

International audience; In inverse problems, the use of an l(12) analysis regularizer induces a bias in the estimated solution. We propose a general refitting framework for removing this artifact while keeping information of interest contained in the biased solution. This is done through the use of refitting block penalties that only act on the co-support of the estimation. Based on an analysis of related works in the literature, we propose a new penalty that is well suited for refitting purposes. We also present an efficient algorithmic method to obtain the refitted solution along with the original (biased) solution for any convex refitting block penalty. Experiments illustrate the good be…

Artifact (error)Total variationComputer scienceRegular polygon02 engineering and technologyInverse problem01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]010104 statistics & probabilityRefitting0202 electrical engineering electronic engineering information engineeringBias correction020201 artificial intelligence & image processingBias correction0101 mathematics[MATH]Mathematics [math]AlgorithmBlock (data storage)Scale Space and Variational Methods in Computer Vision - 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30 – July 4, 2019, Proceedings
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Corrigendum to three papers that deal with “Anti”-Bayesian Pattern Recognition [Pattern Recognition]

2014

In the papers 1 (Thomas and Oommen, 2013), 2 (Oommen and Thomas, 2014) and 3 (Thomas and Oommen, 2013), and their associated conference versions cited in those papers, we had introduced a new method of so-called "Anti"-Bayesian Pattern Recognition (PR) which achieved the classification using only a few (sometimes as few as two) points distant from the mean. While the PR strategy, in and of itself, is accurate, the claim that it was based on the Order Statistics (OS) of the distributions of the features is not. The PR and classification results are rather founded on the symmetric quantiles and not on the symmetric OSs. This brief paper corrects the flawed claim presented in those papers. Hig…

Artificial Intelligencebusiness.industryComputer scienceSignal ProcessingPattern recognition (psychology)Order statisticBayesian probabilityPattern recognitionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareQuantilePattern Recognition
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Using machine learning to disentangle LHC signatures of Dark Matter candidates

2019

We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each other, and against the main SM background ($Z$+jets). Our analysis uses both the leading-order kinematic features as well as the information of an additional hard jet. We explore different representa…

Artificial neural network010308 nuclear & particles physicsbusiness.industryComputer sciencePhysicsQC1-999Dark matterFOS: Physical sciencesGeneral Physics and AstronomySupersymmetryMachine learningcomputer.software_genre01 natural sciencesConvolutional neural networkHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Robustness (computer science)0103 physical sciencesPrincipal component analysisProbability distributionArtificial intelligence010306 general physicsbusinessLight dark mattercomputerSciPost Physics
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State classification for autonomous gas sample taking using deep convolutional neural networks

2017

Despite recent rapid advances and successful large-scale application of deep Convolutional Neural Networks (CNNs) using image, video, sound, text and time-series data, its adoption within the oil and gas industry in particular have been sparse. In this paper, we initially present an overview of opportunities for deep CNN methods within oil and gas industry, followed by details on a novel development where deep CNN have been used for state classification of autonomous gas sample taking procedure utilizing an industrial robot. The experimental results — using a deep CNN containing six layers — show accuracy levels exceeding 99 %. In addition, the advantages of using parallel computing with GP…

Artificial neural networkComputer sciencebusiness.industryProperty (programming)Feature extraction0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesConvolutional neural networklaw.inventionImage (mathematics)Industrial robot020401 chemical engineeringComputer engineering010201 computation theory & mathematicslawProbability distributionArtificial intelligenceState (computer science)0204 chemical engineeringbusinesscomputer2017 25th Mediterranean Conference on Control and Automation (MED)
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