Search results for "simulation model"

showing 10 items of 68 documents

Wastewater Reuse Effects on Soil Hydraulic Conductivity

2004

The wastewater total suspended solids (TSS) concentration effects on the saturated hydraulic conductivity, \iK\ds, of a clay and a loam soil were investigated on laboratory repacked soil cores by a constant head permeameter. Both municipal wastewater (MW) and artificial wastewater (AW) with different TSS concentrations were used, with the aim to evaluate, by comparison, the effects of biological activity. The development of a surface sealed layer was investigated in loam soil columns supplied with AW and equipped with water manometers at different depths to detect the hydraulic head gradient changes. In the loam soil, \iK\ds reduced to about 80% of the initial value after infiltration of 17…

Hydrologysimulation modelswater reuseAgricultural and Biological Sciences (miscellaneous)irrigationInfiltration (hydrology)Hydraulic headWastewaterHydraulic conductivityLoamSoil horizonEnvironmental sciencehydraulic conductivityWater Science and TechnologyCivil and Structural EngineeringTotal suspended solidsPermeameterJournal of Irrigation and Drainage Engineering
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Understanding the shortcomings of commodity-based technology in input-output models: an economic-circuit approach

2004

International audience; The Make-Use Model serves as a basis for most national accounting systems as the System of National Accounts (SNA) and is acknowledged as the most suitable model for interregional analysis. Two hypotheses are traditionally made featuring either industry-based technologies (IBT) or commodity-based technologies (CBT). While industry-based technologies can be easily interpreted in terms of a demand-driven economic circuit, it will be shown that: (1) commodity-based technologies cannot be interpreted as a demand-driven economic circuit because this involves computing the inverse of a matrix (the matrix of industry output proportions), which is either impossible or genera…

Input/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsBasis (linear algebra)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsInput–output modelComputer scienceNational accountsMatrix (music)Environmental Science (miscellaneous)DevelopmentJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financemathematical economicsIndustrial engineeringinput-output analysisdemand (economic theory)JEL : 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 FinanceCommodity (Marxism)Axiom
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Using Hydrus 2-D Simulation model to evaluate wetted soil volume in subsurface drip irrigation systems.

2007

Drip irrigation is considered one of the most efficient irrigation systems. Alternatively to the traditional drip irrigation systems, laterals can be installed below the soil surface. Realizing the subsurface drip irrigation (SDI), which recently has been increasing in use as a consequence of advances in plastics technology, making SDI equipment more affordable and long lasting. Due to its potential high efficiency SDI may produce benefits, especially in places where water is a limited source. As the use of SDI is relatively new, a better understanding of the infiltration process around a buried point source can contribute to increased water use efficiency and consequently the success of dr…

IrrigationHydrusHydraulic engineeringSimulation modelingEnvironmental engineeringDrip irrigationAgricultural and Biological Sciences (miscellaneous)Subsurface drip irrigationInfiltration (hydrology)Soil waterEnvironmental scienceHYDRUS-2D.Water contentWater Science and TechnologyCivil and Structural Engineering
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Biproportional Methods And Interindustry Dynamics: The Case of Energy in France

1996

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q4 - Energy/Q.Q4.Q43 - Energy and the MacroeconomyJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q4 - Energy/Q.Q4.Q43 - Energy and the MacroeconomyJEL: 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: 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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Dynamique de la structure industrielle française

1990

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.C63 - Computational Techniques • Simulation ModelingJEL: 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.C61 - Optimization Techniques • Programming Models • Dynamic AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL: L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price IndicesJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price Indices[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and Finance
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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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