A5102795949- Business Process Modeling and Analysis
- Simulation Techniques and Applications
- Atmospheric aerosols and clouds
- Fish Ecology and Management Studies
- Remote Sensing in Agriculture
- Distributed and Parallel Computing Systems
- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Scientific Computing and Data Management
- Wildlife-Road Interactions and Conservation
- Species Distribution and Climate Change
- Markov Chains and Monte Carlo Methods
- Crystallography and molecular interactions
- Probabilistic and Robust Engineering Design
- Genetic diversity and population structure
- Opinion Dynamics and Social Influence
- Data Management and Algorithms
- Bayesian Methods and Mixture Models
- Software Engineering and Design Patterns
- Model-Driven Software Engineering Techniques
- Advanced Database Systems and Queries
- Terrorism, Counterterrorism, and Political Violence
- Atmospheric chemistry and aerosols
- Solar Radiation and Photovoltaics
- Environmental Impact and Sustainability
Laboratoire Interdisciplinaire Solidarités Sociétés Territoires
2003-2023
Laboratoire d'Ingénierie pour les Systèmes Complexes
2003-2023
Local Initiatives Support Corporation
2006-2015
Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
2014-2015
Laboratoire d'Ingénierie des Systèmes
2010-2014
Université Paris-Sud
2014
Centre National de la Recherche Scientifique
1983-2002
Laboratoire de Météorologie Physique
2002
Université Clermont Auvergne
2001
Université de Montpellier
1983
Sensitivity analysis (SA) is a significant tool for studying the robustness of results and their sensitivity to uncertainty factors in life cycle assessment (LCA). It highlights most important set model parameters determine whether data quality needs be improved, enhance interpretation results. Interactions within LCA calculation correlations Life Cycle Inventory (LCI) input are two main issues among process. Here we propose methodology conducting proper SA which takes into account effects...
Summary Approximate Bayesian computation ( ABC ), a type of likelihood‐free inference, is family statistical techniques to perform parameter estimation and model selection. It increasingly used in ecology evolution, where the models can be too complex handled with standard likelihood techniques. The essence compare simulation outputs observed data, order select values simulations which best fit data. are thus computationally demanding. This constitutes key limitation their implementation. We...
Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates comparison making. Probability-based support in LCA a way their decision-making process. It calculates confidence probability expresses of have impact than one another option. Here we apply reliability theory approximate...
Species can respond to climate change by tracking appropriate environmental conditions in space, resulting a range shift. Distribution Models (SDMs) help forecast such shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa), an endangered anadromous fish is one of them. The main purpose this study was provide framework for joint analyses projections order strengthen conservation measures species concern. Guidelines representation...
In this paper we present OpenMOLE, a scientific framework providing virtualized runtime environment for distributed computing. Current execution systems do not hide the hardware and software heterogeneity of computing data resources whereas OpenMOLE provides generic services to develop algorithms independently from architecture. uses abstraction layers delegate tasks with same high level interface major underlying architectures: local processors, batch systems, computational grids, Internet...
One of the big global, environmental, and socioeconomic challenges today is to make a transition from fossil fuels biomass as sustainable supply renewable raw materials for industry.Growing public awareness negative environmental effects petrochemical-based products adds need alternative production chains, especially in science.One option lies value-added upcycling agricultural byproducts, which are increasingly being used biocomposite transport building sector applications.Here, sunflower...
Abstract. The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. generated outputs are 3-D optical depth (τ) stratocumulus and cumulus ice water content (IWC) cirrus clouds. This model designed to generate that share some statistical properties observed real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by mean of studied quantity), Fourier spectral slope β close −5/3 between smallest scale simulation...
This article describes Simexplorer, a computer framework for managing simulation experiments and, to some extent, the scientific quality of modelling process. An information system, included in framework, insures traceability and their reproducibility thus contributes process management. Moreover, this system provides facilities sharing exchanging components experiment scenarios. The authors illustrate use on simple example
This paper examines the multidimensional modeling of a data warehouse for simulation results. Environmental dynamics is used to study complex scenarios like urbanization, climate change and deforestation while allowing decision makers understand predict evolution environment in response potential value changes large number influence variables. In this context, exploring models produces huge volume data, which must often be studied extensively at different levels aggregation due there being...
In this study, we analyzed the effect of radiative interaction between neighboring pixels on high‐resolution radiant flux bounded cascade inhomogeneous clouds by using a one‐layer mapping neural network as generalized regression analysis. The analysis was done for reflectance, transmittance, and absorptance at different wavelengths under conditions illumination. sign magnitude output coefficients indicate how contribute to target pixel. We found that variation with distance from pixel...
In this study, we evaluated the ability of Mapping Neural Networks (MNNs) to calculate high‐resolution radiant fluxes one‐dimensional and two‐dimensional inhomogeneous clouds. The tests were done for different types clouds, fluxes, wavelengths under conditions illumination. MNNs trained with training data sets composed Monte Carlo (MC) bounded cascade clouds used compute first MC (reflectance, transmittance, absorptance) showed their rather good performance, which was compared that Nonlocal...
Meadows and Cliff (2012) failed to replicate the results of Deffuant et al. (2002) concluded that our paper was wrong. In this note, we show conclusions are due a wrong computation indicator y, which not fully specified in 2002 paper. particular, compute y before model convergence whereas should be computed after convergence.
Abstract. The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. generated outputs are 3-D optical depth (τ) stratocumulus and cumulus ice water content (IWC) cirrus clouds. This model designed to generate that share some statistical properties observed real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by mean of studied quantity), Fourier spectral slope β close −5/3 between smallest scale simulation...