In: Mathematical Geosciences, 2014, vol. 46, no. 5, p. 625-645
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In: Mathematical Geosciences, 2014, vol. 46, no. 2, p. 187-204
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In: Mathematical Geosciences, 2011, vol. 43, no. 3, p. 305-328
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In: Mathematical Geosciences, 2013, vol. 45, no. 2, p. 131-147
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In: Mathematical Geosciences, 2011, vol. 43, no. 8, p. 879-903
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In: Spatial Statistics, 2016, vol. 16, p. 53-71
Multiple-points statistics (MPS) allows to generate random fields reproducing spatial statistics derived from a training image. MPS methods consist in borrowing patterns from the training set. Therefore, the simulation domain is assumed to be at the same resolution as the conceptual model, although geometrical deformations can be handled by such techniques. Whereas punctual conditioning data...
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In: Environmental Modelling & Software, 2016, vol. 86, p. 264-276
The direct sampling (DS) multiple-point statistical technique is proposed as a non-parametric missing data simulator for hydrological flow rate time-series. The algorithm makes use of the patterns contained inside a training data set to reproduce the complexity of the missing data. The proposed setup is tested in the reconstruction of a flow rate time-series while considering several missing data...
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In: Hydrogeology Journal, 2015, vol. 23, no. 5, p. 883-900
The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by...
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In: Geomorphology, 2014, vol. 214, p. 148-156
A new method is proposed to generate successive topographies in a braided river system. Indeed, braided river morphologymodels are a key factor influencing river–aquifer interactions and have repercussions in ecosystems, flood risk or water management. It is essentially based on multivariate multiple-point statistics simulations and digital elevation models as training data sets. On the one...
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In: Computers & Geosciences, 2013, vol. 52, p. 307-324
The Direct Sampling (DS) algorithm is a recently developed multiple-point statistical simulation technique. It directly scans the training image (TI) for a given data event instead of storing the training probability values in a catalogue prior to simulation. By using distances between the given data events and the TI patterns, DS allows to simulate categorical, continuous and multivariate...
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