Search results for "simulation model"

showing 10 items of 68 documents

Comparative study of the efficiency of buffer zones and harvest discarding on gene flow containment in oilseed rape. A modelling approach

2009

International audience; Oilseed rape (OSR) genes can escape fields in space via pollen and seeds and in time via volunteers resulting from seeds lost before or during oilseed rape harvests. Previous simulation studies and field observations showed that co-existence at the landscape level of contrasting OSR varieties such as genetically modified (GM) and non-GM varieties require costly measures that are difficult to implement, such as isolation distances between OSR fields and stringent volunteer control in all fields and road margins. In the present study, two local strategies, non-GM buffer zones aroundGMfields and discarding the harvest of boundary plants of non-GM fields, were tested in …

0106 biological sciences[SDV.SA]Life Sciences [q-bio]/Agricultural sciencesBuffer zoneSoil ScienceHARVEST DISCARDINGPlant Sciencemedicine.disease_cause01 natural sciencesGene flowLandscape levelPollenmedicineGENE FLOWCropping systemBUFFER ZONECOLZAMathematics2. Zero hungerGMOCO-EXISTENCESimulation modeling04 agricultural and veterinary sciences15. Life on landPollen dispersalMODELAgronomy040103 agronomy & agriculture0401 agriculture forestry and fisheriesAgronomy and Crop ScienceCropping010606 plant biology & botany
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A multi-site study to classify semi-natural grassland types

2009

International audience; Calibration and validation of simulation models describing herbage growth or feed quality of seminatural grasslands is a complex task for agronomists without investing effort into botanical surveys. To facilitate such modelling efforts, a limited number of grassland types were identified using a functional classification of species. These grassland types were characterized by three descriptors required to model herbage growth or feed quality: the abundance-weighted mean leaf dry matter content across grass species, the relative abundance of grasses, and an estimate of species richness. We conducted a multi-site analysis over 749 grasslands from eight temperate region…

0106 biological sciencesleaf traitsRestricted maximum likelihoodManagement type01 natural sciencesGrasslandnitrogenland-use changeNutrientSemi-natural grasslandphosphorus2. Zero hunger[SDV.EE]Life Sciences [q-bio]/Ecology environmentgeography.geographical_feature_categoryEcology04 agricultural and veterinary sciencesVegetationClassification[ SDE.MCG ] Environmental Sciences/Global ChangesFunctional traitsplant-species richnessgrowth[SDE.MCG]Environmental Sciences/Global Changespermanent pastures[SDV.BID]Life Sciences [q-bio]/Biodiversity010603 evolutionary biologyEllenberg indicator values[ SDV.EE ] Life Sciences [q-bio]/Ecology environmentdiversity[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsTemperate climateRelative species abundance[ SDV.BID ] Life Sciences [q-bio]/Biodiversitygeography[ SDE.BE ] Environmental Sciences/Biodiversity and EcologySimulation modelingNutrients15. Life on land[SDE.ES]Environmental Sciences/Environmental and Society[ SDV.EE.ECO ] Life Sciences [q-bio]/Ecology environment/EcosystemsAgronomy040103 agronomy & agricultureresponses0401 agriculture forestry and fisheriesEnvironmental scienceAnimal Science and ZoologySpecies richness[SDE.BE]Environmental Sciences/Biodiversity and EcologyAgronomy and Crop Science[ SDE.ES ] Environmental Sciences/Environmental and SocietySpecies richness
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Obtención de los principales parámetros del agua residual urbana empleados en los modelos matemáticos de fangos activados a partir de una caracteriza…

2017

El tratamiento de las aguas residuales se ha realizado en España mediante procesos biológicos como el comúnmente utilizado de fangos activados. Estos procesos han sido descritos mediante modelos matemáticos que describen la eliminación de los contaminantes presentes en el agua (materia orgánica, nitrógeno y fósforo). La utilización de estos modelos requiere de una caracterización detallada de los contaminantes presentes en el agua residual urbana (ARU). La caracterización de un ARU es clave para el uso de estos modelos de simulación, tanto en el diseño como en la simulación de las Estaciones Depuradoras de Aguas Residuales (EDAR). Este trabajo ha utilizado y considerado los parámetros propu…

Activated sludgeWastewaterAigües residualsSimulation modelingEnvironmental engineeringEnvironmental scienceSewage treatmentAigua Qualitat
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Towards the definition of a sustainable Smart Model for the suburbs redevelopment

2020

Starting from the analysis of the problems that characterize the Italian suburbs, the application of a Smart Methodology to a real peripheral area is presented. In literature, several studies underline the urgent request of the city's periphery, enhancing local and national projects to increase the quality of life in the suburbs. In this framework, authors propose a multifunctional centre development, characterized by modern technologies (both structural and plant) to implement energy efficiency and social aggregation, in line with the citizen's needs. Once the simulation model of alternative solutions, such as construction type, energy system and social services, was elaborated in Matlab/S…

Architectural engineeringSettore ING-IND/11 - Fisica Tecnica AmbientaleUnderlineSmart methodology.Computer scienceSuburbs redevelopment0211 other engineering and technologies021107 urban & regional planningSocial Welfare02 engineering and technologyPlan (drawing)010501 environmental sciences01 natural sciencesSmart citieData modelingRankingRedevelopmentSmart methodologySimulation modelSmart cities Suburbs redevelopment Simulation model Smart methodologyEnergy systemsmart cities; suburbs redevelopment; simulation model; smart methodologySmart cities0105 earth and related environmental sciencesEfficient energy use
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The Role of Artificial Intelligence Concepts in System Modelling and Simulation: An Overview

1994

The impact of modelling and simulation methodology research on the daily practice of the simulation community is becoming clearly perceivable. The same applies to the application of the artificial intelligence research in a diversity of computer related fields. As both fields are strongly based on models as the main way they convey their knowledge, the fact of synergy caused by combining these two computer related areas comes as a more or less logical consequence. There is an increasing interest of incorporating methods and techniques developed by and for the artificial intelligence community into modelling and simulation methodology and practice. This paper addresses common aspects and dif…

Artificial architecturebusiness.industryComputer scienceDaily practicemedia_common.quotation_subjectSimulation modelingState (computer science)Artificial intelligencebusinessLogical consequenceDiversity (politics)media_common
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Cropland and grassland management

2014

According to the latest National Inventory, the Italian agricultural sector is a source of GHGs with 34.5 Mt of CO2 eq in 2009, corresponding to 7 % of the total emissions (excluding LULUCF). In particular, more than half (19.1 Mt of CO2 eq) are N2O emissions from soils. Although the national methodology is in accordance with Tier 1 and 2 approaches proposed by the IPCC (2006), still empirical emission factors are used to assess the emission from fertilizer (e.g. 0.0125 kg N2O–N kg−1 N from synthetic fertilizers). Disaggregated data at sub-national level, including models and inventory measurement systems required by higher order methods (i.e. Tier 3), are not available in Italy so far and …

Bilancio del carboniobusiness.industryAgroforestrySimulation modelingEddy covarianceGreenhouse gas inventoryContext (language use)AgricultureSoil carbonSoil carbonGHG balanceModellingAgricolturaSuoloAgricultureGreenhouse gasEnvironmental scienceLand use land-use change and forestryModellisticabusinessWater resource managementSettore AGR/02 - AGRONOMIA E COLTIVAZIONI ERBACEE
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Enchytraeid population dynamics: Resource limitation and size-dependent mortality

2009

Abstract Enchytraeids are regarded as keystone soil organisms in forest ecosystems. Their abundance and biomass fluctuate widely. Predicting the consequences of anthropogenic disturbances requires an understanding of the mechanisms underlying enchytraeid population dynamics. Here I develop a simple model, which predicts that the type of dynamics is controlled by resource input rate. If fungal resource input is a discrete event once a year, an exponential growth phase is followed by starvation and sharp decline of enchytraeid abundance. Model simulations with three different forcing functions were compared to field data. Initial parameter values were obtained from various independent sources…

Biomass (ecology)education.field_of_studyEcologyEcological ModelingPopulationSimulation modelingBiologyAtmospheric sciencesStability (probability)Residual sum of squaresExponential growthAbundance (ecology)Forest ecologyeducationEcological Modelling
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Bicausative matrices to measure structural change: Are they a good tool?

1999

The causative-matrix method to analyze temporal change assumes that a matrix transforms one Markovian transition matrix into another by a left multiplication of the first matrix; the method is demand-driven when applied to input-output economics. An extension is presented without assuming the demand-driven or supply-driven hypothesis. Starting from two flow matrices X and Y, two diagonal matrices are searched, one premultiplying and the second postmultiplying X, to obtain a result the closer as possible to Y by least squares. The paper proves that the method is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. Keywords : Input-Output ; Ch…

BiproportionBicausativePure mathematicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63jel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisLeast squaresMeasure (mathematics)Interpretation (model theory)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingSylvester's law of inertiaMatrix (mathematics)Diagonal matrixStatisticsJEL : 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 FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelseconomic theoryhumanities social sciencessciences humaines et socialesStochastic matrixStructural ChangeGeneral Social Scienceseconomics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57CausativeJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingChaosMultiplicationThe Annals of Regional Science
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Forecast Output Coincidence and Biproportion: Two Criteria to Determine the Orientation of an Economy. Comparison for France (1980-1997)

2002

International audience; The method of forecast output coincidence used to determine if sectors are demand-sided or supply-sided in an input-output framework mixes two effects, the structural effect (choosing between demand and supply side models) and the effect of an exogenous factor (final demand or added-value). The note recalls that another method is possible, the comparison of the stability of technical and allocation coefficients, generalized by the biproportional filter: if for a sector, after biproportional filtering, column coefficients are more stable than row coefficients, then this sector is declared as not supply-sided (but one cannot decide that it is demand-sided anyway), and …

BiproportionEconomics and EconometricsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupplyChangeJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisStability (probability)Column (database)CoincidenceSupply and demandMicroeconomicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingEconometricsEconomicsDemandJEL : 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 FinanceInput/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsOrientation (computer vision)Exogenous factorFilter (signal processing)[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 ModelingInput-OutputRAS
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A biproportional filter to compare technical and allocation coefficient variations

1997

International audience; In input-output analysis there are two alternate possibilities between Leontief's mechanism (fixed technical coefficients) and Ghosh's mechanism (fixed allocation coefficients). Testing the long term consistency of these mechanisms entails comparing input-output matrices over time. This paper challenges the value of proportional filters (separate comparison of column and row coefficients) and introduces the biproportional filter which allows simultaneous comparison of column and rows. An application is proposed using French input-output tables for 1980 and 1993. The stability of column coefficients cannot be taken for granted and generally, for any sector, both rows …

BiproportionSupply-drivenJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsChangeJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)DevelopmentRow and column spacesStability (probability)Column (database)Consistency (statistics)Demand-drivenStatisticsComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONApplied mathematicsJEL : 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 FinanceMathematicsInput/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Models[SHS.ECO]Humanities and Social Sciences/Economics and FinanceTerm (time)Input-OutputFilter (video)RowRAS
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