Search results for "Modelling"
showing 10 items of 1353 documents
Hydrological post-processing based on approximate Bayesian computation (ABC)
2019
[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or …
A Stochastic Soft Constraints Fuzzy Model for a Portfolio Selection Problem
2006
The financial market behavior is affected by several non-probabilistic factors such as vagueness and ambiguity. In this paper we develop a multistage stochastic soft constraints fuzzy program with recourse in order to capture both uncertainty and imprecision as well as to solve a portfolio management problem. The results we obtained confirm the studies carried out in literature addressed to integrate stochastic and possibilistic programming.
Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods
2015
Abstract Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important ( factor prioritisation ) and non-influential ( factor fixing ) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality–quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiar…
MCR-ALS on metabolic networks: Obtaining more meaningful pathways
2015
[EN] With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraint…
Uncertainty Propagation in Integrated Urban Water Quality Modelling
2018
Sensitivity and uncertainty assessment of integrated urban drainage water quality models are crucial steps in the evaluation of the reliability of model results. Indeed, the assessment of the reliability of the results of complex water quality models is crucial in understanding their significance. In the case of integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones in a manner dependent on the model structure, the estimation of parameters and the availability and u…
Global sensitivity analysis in wastewater treatment modelling
2019
Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models. GSA allows the identifcation of the effect of model and input factor uncertainty on the model response, also considering the effect due to the interactions among factors. During recent years, the wastewater modelling feld has embraced the use of GSA. Wastewater modellers have tried to transfer the knowledge and experience from other disciplines and other water modelling felds.
Parasite population delay model of malaria type with stochastic perturbation and environmental criterion for limitation of disease
2009
AbstractWe present a stochastic delay model of an infectious disease (malaria) transmitted by a vectors (mosquitoes) after an incubation time. A criterion for limitation of disease is found.
A fully adaptive multiresolution scheme for image processing
2007
A nonlinear multiresolution scheme within Harten's framework [A. Harten, Discrete multiresolution analysis and generalized wavelets, J. Appl. Numer. Math. 12 (1993) 153-192; A. Harten, Multiresolution representation of data II, SIAM J. Numer. Anal. 33 (3) (1996) 1205-1256] is presented. It is based on a centered piecewise polynomial interpolation fully adapted to discontinuities. Compression properties of the multiresolution scheme are studied on various numerical experiments on images.
Computing continuous numerical solutions of matrix differential equations
1995
Abstract In this paper, we construct analytical approximate solutions of initial value problems for the matrix differential equation X ′( t ) = A ( t ) X ( t ) + X ( t ) B ( t ) + L ( t ), with twice continuously differentiable functions A ( t ), B ( t ), and L ( t ), continuous. We determine, in terms of the data, the existence interval of the problem. Given an admissible error e, we construct an approximate solution whose error is smaller than e uniformly, in all the domain.
Classifying efficient alternatives in SMAA using cross confidence factors
2006
Abstract Stochastic multicriteria acceptability analysis (SMAA) is a family of methods for aiding multicriteria group decision making. These methods are based on exploring the weight space in order to describe the preferences that make each alternative the most preferred one. The main results of the analysis are rank acceptability indices, central weight vectors and confidence factors for different alternatives. The rank acceptability indices describe the variety of different preferences resulting in a certain rank for an alternative; the central weight vectors represent the typical preferences favouring each alternative; and the confidence factors measure whether the criteria data are suff…