Search results for "Simulation."

showing 10 items of 4779 documents

A Note on added information in the RAS Procedure: reexamination of some evidence

2006

International audience; An example in Miernyk (1977) presented a rather counterintuitive result, namely that introducing accurate exogenous information into an RAS matrix estimating procedure could lead to an estimate that was worse than one generated by RAS using no exogenous information at all. This became an oft-cited black mark against RAS. Miller and Blair (1985) included a different (and small) illustration of the same possibility. It was recently pointed out by one of us that the Miller/Blair numerical results are wrong. For that reason, we decided to reexamine all the empirical evidence we could find on the subject. While figures in both Miernyk and Miller/Blair appear to be wrong, …

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsCounterintuitiveClosenessJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)Development[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingInput-outputbiproportionEconometricsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceEmpirical evidenceMathematical economicsCounterexampleMathematicsRAS
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Regional Multicriteria Analysis and Influence Relation

1986

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R0 - GeneralJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R0 - General
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Note about the concept of ‘Net Multipliers'

2002

International audience; Net multipliers, as introduced by Oosterhaven and Stelder (2002) accept outputs as entries instead of final demand. They are found by multiplying ordinary multipliers by the final demand ratio over the sector's output. This pragmatic solution suffers from ratio instability over time. The alternative net multipliers proposed here are based on the interpretation of the Leontief inverse matrix for the effects generated at each round. The new solution is not sensitive to the size of impacts. Now net multiplier is equal to the corresponding ordinary multiplier minus one, and the ordering of multipliers is unchanged.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financeinput-output analysisdemand (economic theory)JEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R15 - Econometric and Input–Output Models • Other ModelsJEL: O - Economic Development Innovation Technological Change and Growth/O.O2 - Development Planning and Policy/O.O2.O20 - GeneralJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances<br />multiplier (economics)Hardware_ARITHMETICANDLOGICSTRUCTURES[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R15 - Econometric and Input–Output Models • Other ModelsJEL : O - Economic Development Innovation Technological Change and Growth/O.O2 - Development Planning and Policy/O.O2.O20 - General
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On Boolean topological methods of structural analysis

2001

The properties of Boolean methods of structural analysis are used to analyze the intern structure of linear or non linear models. Here they are studied on the particular example of qualitative methods of input-output analysis. First, it is shown that these methods generate informational problems like biases when working in money terms instead of percentages, losses of information, increasing of computation time, and so on. Second, considering three ways to do structural analysis, analysis from the inverse matrix, from the direct matrix and from layers (intermediate flow matrices), these methods induce topological problems; the adjacency of the adjacency cannot be defined from the inverse ma…

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelséconomieeconomic theoryjel:C67economicsJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57JEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysisgestion[ SHS.ECO ] Humanities and Social Sciences/Economies and financesMFAmanagement economics[SHS.ECO] Humanities and Social Sciences/Economics and Financemanagementjel:R15
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Biproportion et offre dominante (A propos de l'article d'André Torre ‘Sur la signification théorique du modèle d'offre multisectoriel')

1996

One replies here to partisans of the reject of the supply-driven model in input-output analysis and especially to A. Torre (Revue Economique, 5, 44, 951-970). First of all, demand-driven hypothesis (Leontief) and supply-driven hypothesis (Ghosh) are symmetrical and incompatible, what forbidden to reject the second to the motive that it depends on the first. Secondly, the results earlier obtained for France of 1970 to 1985 from the method of the biproportionnal filter show that there is so much instability in the long term in the columns than in the rows of the flow matrix. Thirdly, the assimilation of the usage of allocation coefficients to the adoption of the supply-side model is excessive.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupply-drivenJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsOffre dominanteInput-outputJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesLeontiefJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceGeneral Economics Econometrics and FinanceGhosh
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A Note on Qualitative Input-Output Analysis

1995

International audience; The paper discusses qualitative input—output methods. It is shown that information is lost. Because the binaiy relationship constructed by qualitative methods is not transitive, the model lacks economic consistency. Qualitative methods are tending to become more sophisticated, but some problems of economic interpretation are raised.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelstopologyJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesQualitative input-outputJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and Finance
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Normalizing biproportional methods

2002

International audience; Biproportional methods are used to update matrices: the projection of a matrix Z to give it the column and row sums of another matrix is R Z S, where R and S are diagonal and secure the constraints of the problem (R and S have no signification at all because they are not identified). However, normalizing R or S generates important mathematical difficulties: it amounts to put constraints on Lagrange multipliers, non negativity (and so the existence of the solution) is not guaranteed at equilibrium or along the path to equilibrium.

JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63Diagonaljel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysismathematical economicsColumn (database)Projection (linear algebra)Combinatoricssymbols.namesakeMatrix (mathematics)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingmatricesJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesNon negativity[SHS.ECO] Humanities and Social Sciences/Economics and FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsGeneral Social Sciences[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57community developmentJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingLagrange multiplierPath (graph theory)symbols
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P2PRealm - Peer-to-Peer Network Simulator

2006

Peer-to-peer realm (P2PRealm) is an efficient peer-to-peer network simulator for studying algorithms based on neural networks. In contrast to many simulators, which emphasize on detailed network simulation, the speed of simulation in P2PRealm is essential, because neural networks require a time consuming training phase. Efficiency has been obtained by optimizing training loops inside the simulator, using Java native interface (JNI) as well as distributing the simulator to hundreds of workstations using the P2PDisCo platform. In this paper we describe the architecture of P2PRealm and its input/output interfaces. Also, we present the mechanisms used for internally optimizing the implementatio…

JavaComputer architecture simulatorWorkstationArtificial neural networkComputer scienceJava Native InterfaceDistributed computingPeer-to-peercomputer.software_genreNetwork simulationlaw.inventionvertaisverkkosimulaattorilawcomputerPower system simulator for engineeringcomputer.programming_language2006 11th Intenational Workshop on Computer-Aided Modeling, Analysis and Design of Communication Links and Networks
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XTDS and SPVIEW: Graphical tools for the analysis and simulation of high-resolution molecular spectra

2008

International audience; XTDS is a Java front-end to the different programs implementing the tensorial formalism developed in the Dijon group [see for instance: V. Boudon, J.-P. Champion, T. Gabard, M. Loëte, F. Michelot, G. Pierre, M. Rotger, Ch. Wenger, M. Rey, J. Mol. Spectrosc. 228 (2004) 620–634 ]. It allows the simulation and analysis of polyad systems for molecules of various symmetries (Td and Oh spherical tops like CH4 and SF6, C2v and C4v quasi-spherical tops like SO2F2 and SF5Cl, D2h molecules like C2H4). SPVIEW is a multiplatform Java application that allows graphical assignment of high-resolution molecular spectra. It is possible to load, display and manipulate experimental and …

JavaComputer scienceTensorial formalism02 engineering and technologyASCII01 natural sciencesGraphical toolsSpectral lineComputational scienceSoftware0103 physical sciencesGraphical interfaceAnalysis and simulationPhysical and Theoretical ChemistrySpectroscopyGraphical user interfacecomputer.programming_language[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]010304 chemical physicsbusiness.industrySpectrum assignment021001 nanoscience & nanotechnologyAtomic and Molecular Physics and Optics[ PHYS.PHYS.PHYS-AO-PH ] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]Homogeneous spaceHITRAN0210 nano-technologybusinesscomputer
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Dominància i ocupació de l'espai en grups de primats no-humans: un model basat en conducta adaptativa

2007

L'estructura jeràrquica és una de les característiques fonamentals de les societats de primats, que condiciona en gran mesura el comportament dels individus que conviuen al grup. Quines lleis regeixen la formació i l'estructura d'aquestes jerarquies? Per què en determinats grups els subjectes més dominants se situen al centre del grup i en uns altres de la mateixa espècie no? En el camp de la conducta animal s'han proposat múltiples hipòtesis, però no n'hi ha cap que siga totalment satisfactòria, ja que a causa de les múltiples variables que hi infl ueixen, és difícil desplegar una teoria que explique tota la complexitat que s'observa empíricament. La nostra proposta d'estudi es basa en l'e…

Jerarquia social en els animalsPrimatesjerarquia conducta espacial primats no humans conducta adaptativa simulació. hierarchy spatial behavior non-human primates adaptive behavior simulation. ArtículoEtologiaSpatial behaviorPrimatsConducta espacial:PSICOLOGÍA [UNESCO]UNESCO::PSICOLOGÍAAnimal behaviorSocial hierarchy in animals
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