Search results for "approximation"

showing 10 items of 818 documents

New fitting scheme to obtain effective potential from Car-Parrinello molecular dynamics simulations: Application to silica

2008

A fitting scheme is proposed to obtain effective potentials from Car-Parrinello molecular dynamics (CPMD) simulations. It is used to parameterize a new pair potential for silica. MD simulations with this new potential are done to determine structural and dynamic properties and to compare these properties to those obtained from CPMD and a MD simulation using the so-called BKS potential. The new potential reproduces accurately the liquid structure generated by the CPMD trajectories, the experimental activation energies for the self-diffusion constants and the experimental density of amorphous silica. Also lattice parameters and elastic constants of alpha-quartz are well-reproduced, showing th…

Car–Parrinello molecular dynamicsMaterials sciencemolecular dynamics calculations (Car-Parrinello) and other numerical simulationsTransferabilityGeneral Physics and AstronomyFOS: Physical sciences02 engineering and technologyglasses01 natural sciencesMolecular physicsMolecular dynamicsLattice (order)0103 physical sciences[PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]010306 general physicsdensity functional theoryCondensed Matter - Materials Sciencegradient and other correctionsMaterials Science (cond-mat.mtrl-sci)Disordered Systems and Neural Networks (cond-mat.dis-nn)computer simulation of liquid structureCondensed Matter - Disordered Systems and Neural Networks021001 nanoscience & nanotechnologylocal density approximation[PHYS.COND.CM-MS]Physics [physics]/Condensed Matter [cond-mat]/Materials Science [cond-mat.mtrl-sci]Amorphous silica0210 nano-technologyPair potential
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Analytic calculation of the diagonal Born-Oppenheimer correction within configuration-interaction and coupled-cluster theory

2006

Schemes for the analytic calculation of the diagonal Born-Oppenheimer correction (DBOC) are formulated and implemented for use with general single-reference configuration-interaction and coupled-cluster wave function models. Calculations are reported to demonstrate the convergence of the DBOC with respect to electron-correlation treatment and basis set as well as to investigate the size-consistency error in configuration-interaction calculations of the DBOC. The importance of electron-correlation contributions to the DBOC is illustrated in the computation of the corresponding corrections for the reaction energy and activation barrier of the F + H2 --FH + H reaction as well as of the atomiza…

ChemistryComputationDiagonalBorn–Oppenheimer approximationGeneral Physics and AstronomyConfiguration interactionsymbols.namesakeCoupled clusterQuantum electrodynamicsConvergence (routing)symbolsPhysical and Theoretical ChemistryAtomic physicsWave functionBasis setThe Journal of Chemical Physics
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Artificial neural network for quantitative determination of total protein in yogurt by infrared spectrometry

2009

Abstract A method has been introduced for quantitative determination of protein content in yogurt samples based on the characteristic absorbance of protein in 1800–1500 cm− 1 spectral region by mid-FTIR spectroscopy and chemometrics. Successive Projection Algorithm (SPA) wavelength selection procedure, coupled with feed forward Back-Propagation Artificial Neural Network (BP-ANN) model was the benefited chemometric technique. Relative Error of Prediction (REP) in BP-ANN and SPA-BP-ANN methods for training set was 7.25 and 3.70 respectively. Considering the complexity of the sample, the ANN model was found to be reliable, while the proposed method is rapid and simple, without any sample prepa…

ChemometricsAbsorbanceChromatographyArtificial neural networkChemistryApproximation errorSample preparationBiological systemQuantitative analysis (chemistry)SpectroscopyBackpropagationDykstra's projection algorithmAnalytical ChemistryMicrochemical Journal
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Prediction of peak shape as a function of retention in reversed-phase liquid chromatography

2004

Optimisation of the resolution of multicomponent samples in HPLC is usually carried out by changing the elution conditions and considering the variation in retention of the analytes, to which a standard peak shape is assigned. However, the change in peak shape with the composition of the mobile phase can ruin the optimisation process, yielding unexpected overlaps in the experimental chromatograms for the predicted optimum, especially for complex mixtures. The possibility of modelling peak shape, in addition to peak position, is therefore attractive. A simple modified-Gaussian model with a parabolic variance, which is a function of conventional experimental parameters: retention time (tR), p…

ChromatographyElutionChemistryOrganic ChemistryResolution (electron density)Analytical chemistryGeneral MedicineReversed-phase chromatographyFunction (mathematics)Models TheoreticalBiochemistryHigh-performance liquid chromatographyStandard deviationAnalytical ChemistryApproximation errorPhase (matter)Chromatography LiquidJournal of Chromatography A
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Upper Bound for the Approximation Error for the Kirchhoff-Love Arch Problem

2013

In this paper, a guaranteed and computable upper bound of approximation errors for the Kirchhoff-Love arch problem is derived. In general, it belongs to the class of functional a posteriori error estimates. The derivation method uses purely functional arguments and, therefore, the estimates are valid for any conforming approximation within the energy space. The computational implementation of the upper bound is discussed and demonstrated by a numerical example.

Class (set theory)Approximation errorA priori and a posterioriApplied mathematicsDerivation methodArchSpace (mathematics)Upper and lower boundsEnergy (signal processing)Mathematics
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Model approximation for two-dimensional Markovian jump systems with state-delays and imperfect mode information

2014

Published version of an article in the journal: Multidimensional Systems and Signal Processing. Also available from the publisher at: http://dx.doi.org/10.1007/s11045-013-0276-x This paper is concerned with the problem of {Mathematical expression} model approximation for a class of two-dimensional (2-D) discrete-time Markovian jump linear systems with state-delays and imperfect mode information. The 2-D system is described by the well-known Fornasini-Marchesini local state-space model, and the imperfect mode information in the Markov chain simultaneously involves the exactly known, partially unknown and uncertain transition probabilities. By using the characteristics of the transition proba…

Class (set theory)Mathematical optimizationMarkov chainmodel approximationApplied Mathematicstwo-dimensional systemsMarkovian jump systemsRegular polygonMode (statistics)imperfect mode informationState (functional analysis)VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Computer Science ApplicationsMarkovian jumpMarkovian jump linear systemsArtificial IntelligenceHardware and ArchitectureSignal ProcessingApplied mathematicsstate-delaysImperfectSoftwareInformation SystemsMathematics
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Approximating hidden chaotic attractors via parameter switching.

2018

In this paper, the problem of approximating hidden chaotic attractors of a general class of nonlinear systems is investigated. The parameter switching (PS) algorithm is utilized, which switches the control parameter within a given set of values with the initial value problem numerically solved. The PS-generated attractor approximates the attractor obtained by averaging the control parameter with the switched values, which represents the hidden chaotic attractor. The hidden chaotic attractors of a generalized Lorenz system and the Rabinovich-Fabrikant system are simulated for illustration. In Refs. 1–3, it is proved that the attractors of a chaotic system, considered as the unique numerical …

Class (set theory)Mathematics::Dynamical SystemsChaoticGeneral Physics and AstronomyFOS: Physical sciences01 natural sciences010305 fluids & plasmasSet (abstract data type)phase space methods0103 physical sciencesAttractorApplied mathematicsInitial value problemdifferentiaalilaskenta010301 acousticsMathematical PhysicsMathematicsApplied Mathematicsta111numerical approximationsStatistical and Nonlinear Physicschaotic systemsLorenz systemchaoticNonlinear Sciences - Chaotic DynamicsNonlinear Sciences::Chaotic DynamicsNonlinear systemkaaosnumeerinen analyysinonlinear systemsChaotic Dynamics (nlin.CD)Chaos (Woodbury, N.Y.)
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Relaxation for a Class of Control Systems with Unilateral Constraints

2019

We consider a nonlinear control system involving a maximal monotone map and with a priori feedback. We assume that the control constraint multifunction $U(t,x)$ is nonconvex valued and only lsc in the $x \in \mathbb{R}^{N}$ variable. Using the Q-regularization (in the sense of Cesari) of $U(t,\cdot )$, we introduce a relaxed system. We show that this relaxation process is admissible.

Class (set theory)Partial differential equationApplied Mathematics010102 general mathematicsMaximal monotone mapNonlinear control01 natural sciencesAdmissible relaxation010101 applied mathematicsConstraint (information theory)CombinatoricsMonotone polygonQ-regularizationSettore MAT/05 - Analisi MatematicaControl systemRelaxation (approximation)0101 mathematicsLower semicontinuous multifunctionVariable (mathematics)MathematicsContinuous selection
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Emergent Collective Behaviors in a Multi-agent Reinforcement Learning Pedestrian Simulation: A Case Study

2015

In this work, a Multi-agent Reinforcement Learning framework is used to generate simulations of virtual pedestrians groups. The aim is to study the influence of two different learning approaches in the quality of generated simulations. The case of study consists on the simulation of the crossing of two groups of embodied virtual agents inside a narrow corridor. This scenario is a classic experiment inside the pedestrian modeling area, because a collective behavior, specifically the lanes formation, emerges with real pedestrians. The paper studies the influence of different learning algorithms, function approximation approaches, and knowledge transfer mechanisms on performance of learned ped…

Collective behaviorFunction approximationbusiness.industryComputer scienceBellman equationVector quantizationProbabilistic logicReinforcement learningArtificial intelligencebusinessTransfer of learningKnowledge transferSimulation
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A Characterization of Bispecial Sturmian Words

2012

A finite Sturmian word w over the alphabet {a,b} is left special (resp. right special) if aw and bw (resp. wa and wb) are both Sturmian words. A bispecial Sturmian word is a Sturmian word that is both left and right special. We show as a main result that bispecial Sturmian words are exactly the maximal internal factors of Christoffel words, that are words coding the digital approximations of segments in the Euclidean plane. This result is an extension of the known relation between central words and primitive Christoffel words. Our characterization allows us to give an enumerative formula for bispecial Sturmian words. We also investigate the minimal forbidden words for the set of Sturmian wo…

CombinatoricsChristoffel symbolsApproximations of πEuclidean geometrySturmian wordAlphabetMathematicsSturmian words Christoffel words special factors minimal forbidden words enumerative formula
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