Search results for "Modell"

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…

New analytical approach to analyze the nonlinear regime of stochastic resonance

2015

We propose some approximate methods to explore the nonlinear regime of the stochastic resonance phenomenon. These approximations correspond to different truncation schemes of cumulants. We compare the theoretical results for the signal power amplification, obtained by using ordinary cumulant truncation schemes, that is Gaussian and excess approximations, the modified two-state approximation with those obtained by numerical simulations of the Langevin equation describing the dynamics of the system.

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…

Meccanismi di distribuzione e sopravvivenza del Grillaio (Falco naumanni) in un agro – ecosistema del Mediterraneo

La distribuzione spaziale degli animali nel loro ambiente naturale ha da sempre attratto l’interesse degli studiosi di ecologia animale e dei biologi della conservazione. Infatti, i meccanismi di selezione dell’habitat possono influenzare processi ecologici di base come la regolazione delle popolazioni e l’andamento demografico, che in ultima analisi, possono agire sulla selezione naturale, la variabilità genetica e il flusso genico. Le principali teorie sulla distribuzione spaziale degli animali affermano che la qualità degli habitat è eterogenea e che gli organismi vanno alla ricerca di territori di elevata qualità al fine di ottimizzare la fitness. La ricerca da parte degli animali di ha…

Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II

2022

Detailed parametric analysis and measurements are required to reduce building energy usage while maintaining acceptable thermal conditions. This research suggested a system that combines Building Information Modeling (BIM), machine learning, and the non-dominated sorting genetic algorithm-II (NSGA II) to investigate the impact of building factors on energy usage and find the optimal design. A plugin is developed to receive sensor data and export all necessary information from BIM to MSSQL and Excel. The BIM model was imported to IDA Indoor Climate and Energy (IDA ICE) to execute an energy consumption simulation and then a pairwise test to produce the sample data set. To study the data set a…