Search results for "approximation error"

showing 10 items of 62 documents

Factor selection procedures in a Google Earthtm aided landslide susceptibility model: application to the Beiro river basin (Spain)

2011

A procedure to select the controlling factors connected to the slope instability has been defined. It allowed to assess the landslide susceptibility in the Rio Beiro basin (about 10 km2) over the north-eastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed to generate a landslide inventory consisting in 127 phenomena. Univariate tests, using both association coefficients and validation results of single parameter susceptibility models, allowed to select among 15 controlling factors the ones that resulted as good predictor variables; these have been combined for unique conditions analysis and susceptibility maps were finally prepared. In…

multivariate landslide susceptibility models conditional analysis controlling factor selection model validation Google EarthTm.geography.geographical_feature_categorySettore GEO/04 - Geografia Fisica E GeomorfologiaUnivariateDrainage basinForecast skillLandslideLandslide susceptibilityField (geography)GeographyGoodness of fitApproximation errorStatisticsCartography
researchProduct

On Equivalent Random Traffic method extension

2011

The key result of the paper is the Equivalent Random Traffic (ERT) method extension for estimation of the throughput for schemes with traffic splitting. The excellent accuracy (relative error is less than 1%) is shown in numerical example. A numerical algorithm is given — how to estimate the throughput for schemes at traffic splitting and merging. The paper also contains new Erlang-B formula algorithm for non-integer number of channels based on parabolic approximation.

Mathematical optimizationApproximation errorTelecommunication channelsNumerical analysisComputer Science::Networking and Internet ArchitectureKey (cryptography)Integrated opticsExtension (predicate logic)Throughput (business)Erlang (unit)AlgorithmMathematics2011 Baltic Congress on Future Internet and Communications
researchProduct

Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension

2016

We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…

0209 industrial biotechnologyStochastic stabilityMathematical optimizationCollective behaviorTechnologyComputer sciencePopulationcontrol designcrowd-averse robust mean-field games state space extension dynamic agents linear stochastic differential equation Brownian motion adversarial disturbance cost functional cross-coupling mean-field term collective behavior stock market application production engineering example dynamic demand management problem robust mean-field game approximation error stochastic stability microscopic dynamics macroscopic dynamicscontrol engineering02 engineering and technology01 natural sciencesStochastic differential equationoptimal control020901 industrial engineering & automationQuadratic equationAutomation & Control SystemsEngineeringClosed loop systemsSettore ING-INF/04 - AutomaticaApproximation errorRobustness (computer science)Control theory0102 Applied MathematicsState space0101 mathematicsElectrical and Electronic EngineeringeducationBrownian motioneducation.field_of_studyScience & TechnologyStochastic process010102 general mathematicsRelaxation (iterative method)Engineering Electrical & ElectronicOptimal controlComputer Science Applications0906 Electrical and Electronic EngineeringIndustrial Engineering & AutomationMean field theoryControl and Systems EngineeringSettore MAT/09 - Ricerca Operativa0913 Mechanical Engineering
researchProduct

Fuzzy Variable Structure Control for Uncertain Systems with Disturbance

2012

Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/105074 This paper focuses on the fuzzy variable structure control for uncertain systems with disturbance. Specifically, the fuzzy control is introduced to estimate the control disturbance, the switching control is included to compensate for the approximation error, and they possess the characteristic of simpleness in design and effectiveness in attenuating the control chattering. Some typical numerical examples are presented to demonstrate the effectiveness and advantage of the fuzzy variable structure controller proposed.

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Variable structure controlEngineeringDisturbance (geology)Article Subjectbusiness.industrylcsh:MathematicsGeneral MathematicsVDP::Technology: 500General EngineeringControl engineeringFuzzy control systemlcsh:QA1-939Fuzzy logicVariable (computer science)Single-input single-output systemlcsh:TA1-2040Approximation errorControl theorylcsh:Engineering (General). Civil engineering (General)businessMathematical Problems in Engineering
researchProduct

Effective axial-vector strength and β -decay systematics

2014

We use the weak axial-vector coupling strength as a key parameter to reproduce simultaneously the available data for both the Gamow-Teller and decay rates in nine triplets of isobars with mass numbers . We use the proton-neutron quasiparticle random-phase approximation (pnQRPA) with schematic dipole interaction containing particle-particle and particle-hole parts with mass-dependent strengths. Our analysis points to a strongly quenched effective value , with a relative error of 28%. We then perform a systematic computation of 218 experimentally known and decays with quite a remarkable success. The presently extracted value of should be taken as an effective one, specific for a given nuclear…

PhysicsDipoleApproximation errorComputationGiant resonanceNuclear TheoryQuasiparticleIsobarGeneral Physics and AstronomyAtomic physicsPseudovectorExcitationEPL (Europhysics Letters)
researchProduct

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals

2005

Several interlinked algorithms for peak deconvolution by non-linear regression are presented. These procedures, together with the peak detection methods outlined in Part I, have allowed the implementation of an automatic method able to process multi-overlapped signals, requiring little user interaction. A criterion based on the evaluation of the multivariate selectivity of the chromatographic signal is used to auto-select the most efficient deconvolution procedure for each chromatographic situation. In this way, non-optimal local solutions are avoided in cases of high overlap, and short computation times are obtained in situations of high resolution. A new algorithm, fitting both the origin…

Blind deconvolutionPolynomialPropagation of uncertaintyChromatographySeries (mathematics)business.industryNoise (signal processing)ChemistryGaussianOrganic ChemistryGeneral MedicineAutomationBiochemistryPeak detectionAnalytical Chemistrysymbols.namesakeLocal optimumApproximation errorsymbolsDeconvolutionbusinessAlgorithmSmoothingSecond derivativeJournal of Chromatography A
researchProduct

Higher Degree F-transforms Based on B-splines of Two Variables

2016

The paper deals with the higher degree fuzzy transforms (F-transforms with polynomial components) for functions of two variables in the case when two-dimensional generalized fuzzy partition is given by B-splines of two variables. We investigate properties of the direct and inverse F-transform in this case and prove that using B-splines as basic functions of fuzzy partition allows us to improve the quality of approximation.

0209 industrial biotechnologyPolynomialDegree (graph theory)Inverse02 engineering and technologyFuzzy partitionFuzzy logic020901 industrial engineering & automationQuality (physics)Approximation error0202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processingMathematics
researchProduct

Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)

2020

The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. A parameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of …

Earth observation010504 meteorology & atmospheric sciencesWater stressSEVIRI/MSG0211 other engineering and technologiesEddy covariance02 engineering and technology01 natural sciences114 Physical sciencesApproximation errorMGPP10-dayComputers in Earth SciencesEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingPrimary production15. Life on landAtomic and Molecular Physics and OpticsComputer Science ApplicationsPhotosynthetically active radiationProduct (mathematics)Geostationary orbitEnvironmental scienceLSA SAFSatelliteGPPLight-use efficiency
researchProduct

An adaption mechanism for the error threshold of XCSF

2020

Learning Classifier System (LCS) is a class of rule-based learning algorithms, which combine reinforcement learning (RL) and genetic algorithm (GA) techniques to evolve a population of classifiers. The most prominent example is XCS, for which many variants have been proposed in the past, including XCSF for function approximation. Although XCSF is a promising candidate for supporting autonomy in computing systems, it still must undergo parameter optimization prior to deployment. However, in case the later deployment environment is unknown, a-priori parameter optimization is not possible, raising the need for XCSF to automatically determine suitable parameter values at run-time. One of the mo…

education.field_of_studyLearning classifier systemComputer sciencePopulation0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesSet (abstract data type)Function approximation010201 computation theory & mathematicsApproximation errorGenetic algorithm0202 electrical engineering electronic engineering information engineeringReinforcement learning020201 artificial intelligence & image processingeducationAlgorithmProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
researchProduct

Quantitative approximation of certain stochastic integrals

2002

We approximate certain stochastic integrals, typically appearing in Stochastic Finance, by stochastic integrals over integrands, which are path-wise constant within deterministic, but not necessarily equidistant, time intervals. We ask for rates of convergence if the approximation error is considered in L 2 . In particular, we show that by using non-equidistant time nets, in contrast to equidistant time nets, approximation rates can be improved considerably.

Physics::Computational PhysicsMeasurable functionRate of convergenceApproximation errorPath integral formulationMathematical analysisEquidistantStochastic approximationConstant (mathematics)Brownian motionMathematicsStochastics and Stochastic Reports
researchProduct