Search results for "Calculus"

showing 10 items of 617 documents

MAST solution of advection problems in irrotational flow fields

2007

Abstract A new numerical–analytical Eulerian procedure is proposed for the solution of convection-dominated problems in the case of existing scalar potential of the flow field. The methodology is based on the conservation inside each computational elements of the 0th and 1st order effective spatial moments of the advected variable. This leads to a set of small ODE systems solved sequentially, one element after the other over all the computational domain, according to a MArching in Space and Time technique. The proposed procedure shows the following advantages: (1) it guarantees the local and global mass balance; (2) it is unconditionally stable with respect to the Courant number, (3) the so…

Eulerian methods convective flow computational methodsComputer scienceAdvectionNumerical analysisCourant–Friedrichs–Lewy conditionOdeScalar potentialEulerian pathConservative vector fieldsymbols.namesakeMonotone polygonCalculussymbolsApplied mathematicsWater Science and Technology
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Une quête d'exactitude : machines, algèbre et géométrie pour la construction traditionnelle des équations différentielles

2015

In La Géométrie, Descartes proposed a “balance” between geometric constructions and symbolic manipulation with the introduction of suitable ideal machines. In particular, Cartesian tools were polynomial algebra (analysis) and a class of diagrammatic constructions (synthesis). This setting provided a classification of curves, according to which only the algebraic ones were considered “purely geometrical.” This limit was overcome with a general method by Newton and Leibniz introducing the infinity in the analytical part, whereas the synthetic perspective gradually lost importance with respect to the analytical one—geometry became a mean of visualization, no longer of construction. Descartes’s…

Exactness problemGeometrical constructionsMouvement tractionnelTraditional motionConstructions géométriquesDescartes[SHS.PHIL]Humanities and Social Sciences/Philosophyexactness problem tractional motion differential algebra Descartes' geometry. differential equationsDifferential algebraIdeal machinesArtefacts in math educationFoundations of calculus
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Language-Game: Calculus or Pragmatic Act?

2013

We have tried to make the potentiality inherent in the concept of the linguistic game evident by taking it back to its original context in the work of Wittgenstein. This paper aims to re-examine some features of Wittgenstein’s thought, considering in particular the notion of ‘language-game’. We believe that the language-game might play a role in overcoming once and for all the classic distinction between semantics and pragmatics. We deal with the exegetical discussion of the notion ‘language-game’ as it was interpreted in two different senses: as a synonym of calculus or as a minimal unit of linguistic activity that is directed to obtaining certain pragmatic effects in a societal context. T…

Expression (architecture)Interpretation (philosophy)CalculusLanguage-gameSociologySign languagePragmaticsSemanticsSymbol (formal)Gesture
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Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability

2020

Despite significant effort, building models that are both interpretable and accurate is an unresolved challenge for many pattern recognition problems. In general, rule-based and linear models lack accuracy, while deep learning interpretability is based on rough approximations of the underlying inference. Using a linear combination of conjunctive clauses in propositional logic, Tsetlin Machines (TMs) have shown competitive performance on diverse benchmarks. However, to do so, many clauses are needed, which impacts interpretability. Here, we address the accuracy-interpretability challenge in machine learning by equipping the TM clauses with integer weights. The resulting Integer Weighted TM (…

FOS: Computer and information sciencesBoosting (machine learning)Theoretical computer scienceinteger-weighted Tsetlin machineGeneral Computer ScienceComputer scienceComputer Science - Artificial Intelligence0206 medical engineeringNatural language understandingInference02 engineering and technologycomputer.software_genre0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceTsetlin machineVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550InterpretabilityArtificial neural networkLearning automatabusiness.industryDeep learningGeneral Engineeringinterpretable machine learningrule-based learninginterpretable AIPropositional calculusSupport vector machineArtificial Intelligence (cs.AI)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESXAIPattern recognition (psychology)020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligencebusinesslcsh:TK1-9971computer020602 bioinformaticsInteger (computer science)
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On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators

2020

The Tsetlin Machine (TM) is a recent machine learning algorithm with several distinct properties, such as interpretability, simplicity, and hardware-friendliness. Although numerous empirical evaluations report on its performance, the mathematical analysis of its convergence is still open. In this article, we analyze the convergence of the TM with only one clause involved for classification. More specifically, we examine two basic logical operators, namely, the "IDENTITY"- and "NOT" operators. Our analysis reveals that the TM, with just one clause, can converge correctly to the intended logical operator, learning from training data over an infinite time horizon. Besides, it can capture arbit…

FOS: Computer and information sciencesComputer Science - Machine LearningTraining setLearning automataComputer Science - Artificial IntelligenceComputer sciencebusiness.industryApplied MathematicsTime horizonPropositional calculusLogical connectiveMachine Learning (cs.LG)Artificial Intelligence (cs.AI)Operator (computer programming)Computational Theory and MathematicsArtificial IntelligencePattern recognition (psychology)Convergence (routing)Identity (object-oriented programming)Computer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareInterpretabilityIEEE Transactions on Pattern Analysis and Machine Intelligence
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Fractional generalized cumulative entropy and its dynamic version

2021

Following the theory of information measures based on the cumulative distribution function, we propose the fractional generalized cumulative entropy, and its dynamic version. These entropies are particularly suitable to deal with distributions satisfying the proportional reversed hazard model. We study the connection with fractional integrals, and some bounds and comparisons based on stochastic orderings, that allow to show that the proposed measure is actually a variability measure. The investigation also involves various notions of reliability theory, since the considered dynamic measure is a suitable extension of the mean inactivity time. We also introduce the empirical generalized fract…

FOS: Computer and information sciencesExponential distributionComputer Science - Information TheoryMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesMeasure (mathematics)010305 fluids & plasmas0103 physical sciencesFOS: MathematicsApplied mathematicsAlmost surelyCumulative entropy; Fractional calculus; Stochastic orderings; EstimationEntropy (energy dispersal)010306 general physicsStochastic orderingsMathematicsCentral limit theoremNumerical AnalysisInformation Theory (cs.IT)Applied MathematicsCumulative distribution functionProbability (math.PR)Fractional calculusEmpirical measureFractional calculusModeling and SimulationEstimationCumulative entropyMathematics - ProbabilityCommunications in Nonlinear Science and Numerical Simulation
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Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

2012

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.

FOS: Computer and information sciencesMultivariate wind velocity fieldMultivariate statisticsStatistical Mechanics (cond-mat.stat-mech)Fractional spectral momentRenewable Energy Sustainability and the EnvironmentMechanical EngineeringMathematical analysisFOS: Physical sciencesGeneralized Taylor formWhite noiseFunction (mathematics)Digital simulation of Gaussian stationary processeFractional calculuStatistics - ComputationTransfer functionWind speedFractional calculusSuperposition principleSettore ICAR/08 - Scienza Delle CostruzioniComputation (stat.CO)Condensed Matter - Statistical MechanicsLinear filterCivil and Structural EngineeringMathematics
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Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach

2021

Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but important extensions that have not been considered in the literature. To tackle these new settings, we present a search algorithm directly over the rules of do-calculus. Due to generality of do-calculus, the search is capable of taking more advanced data-generating mechanisms into account along with an arbitrary type of both observational and…

FOS: Computer and information sciencesStatistics and ProbabilityComputer Science - Machine LearningcausalityComputer Science - Artificial IntelligenceHeuristic (computer science)Computer scienceeducationMachine Learning (stat.ML)transportabilitycomputer.software_genre01 natural sciencesMachine Learning (cs.LG)R-kielimissing dataQA76.75-76.765; QA273-280010104 statistics & probabilitydo-calculuscausality; do-calculus; selection bias; transportability; missing data; case-control design; meta-analysisStatistics - Machine LearningSearch algorithmselection bias0101 mathematicsParametric statisticspäättelymeta-analyysicase-control designhakualgoritmit113 Computer and information sciencesMissing datameta-analysisIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiabilityProbability distributionData miningStatistics Probability and UncertaintycomputerSoftwareJournal of Statistical Software
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Surrogate outcomes and transportability

2019

Identification of causal effects is one of the most fundamental tasks of causal inference. We consider an identifiability problem where some experimental and observational data are available but neither data alone is sufficient for the identification of the causal effect of interest. Instead of the outcome of interest, surrogate outcomes are measured in the experiments. This problem is a generalization of identifiability using surrogate experiments and we label it as surrogate outcome identifiability. We show that the concept of transportability provides a sufficient criteria for determining surrogate outcome identifiability for a large class of queries.

FOS: Computer and information scienceskokeilucausalityGeneralizationComputer scienceComputer Science - Artificial Intelligence02 engineering and technologyMachine learningcomputer.software_genreOutcome (game theory)Theoretical Computer ScienceMethodology (stat.ME)do-calculusArtificial Intelligence020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringStatistics - Methodologyta113päättelyta112experimentbusiness.industrySurrogate endpointverkkoteoriaApplied MathematicsCausal effectta111graphidentifiabilityIdentification (information)Artificial Intelligence (cs.AI)Causal inferencekausaliteettiIdentifiability020201 artificial intelligence & image processingObservational studyArtificial intelligencebusinessmediatorcomputerSoftware
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On differences and similarities in the analysis of Lorenz, Chen, and Lu systems

2015

Currently it is being actively discussed the question of the equivalence of various Lorenz-like systems and the possibility of universal consideration of their behavior (Algaba et al., 2013a,b, 2014b,c; Chen, 2013; Chen and Yang, 2013; Leonov, 2013a), in view of the possibility of reduction of such systems to the same form with the help of various transformations. In the present paper the differences and similarities in the analysis of the Lorenz, the Chen and the Lu systems are discussed. It is shown that the Chen and the Lu systems stimulate the development of new methods for the analysis of chaotic systems. Open problems are discussed.

FOS: Physical sciencesLyapunov exponentLorenz-like systemsLu systemChaotic analog of 16th Hilbert problemReduction (complexity)symbols.namesakeChenDevelopment (topology)Lorenz systemChaotic systemsCalculusApplied mathematicsEquivalence (measure theory)MathematicsbiologyApplied Mathematicsta111Lorenz systembiology.organism_classificationNonlinear Sciences - Chaotic DynamicsComputational MathematicsChen systemsymbolsChaotic Dynamics (nlin.CD)Lyapunov exponentApplied Mathematics and Computation
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