Search results for "modelling"
showing 10 items of 1353 documents
On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization
2019
Many works on surrogate-assisted evolutionary multiobjective optimization have been devoted to problems where function evaluations are time-consuming (e.g., based on simulations). In many real-life optimization problems, mathematical or simulation models are not always available and, instead, we only have data from experiments, measurements or sensors. In such cases, optimization is to be performed on surrogate models built on the data available. The main challenge there is to fit an accurate surrogate model and to obtain meaningful solutions. We apply Kriging as a surrogate model and utilize corresponding uncertainty information in different ways during the optimization process. We discuss…
Handling expensive multiobjective optimization problems with evolutionary algorithms
2017
Multiobjective optimization problems (MOPs) with a large number of conflicting objectives are often encountered in industry. Moreover, these problem typically involve expensive evaluations (e.g. time consuming simulations or costly experiments), which pose an extra challenge in solving them. In this thesis, we first present a survey of different methods proposed in the literature to handle MOPs with expensive evaluations. We observed that most of the existing methods cannot be easily applied to problems with more than three objectives. Therefore, we propose a Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) for problems with at least three expensive objectives. The alg…
Probabilistic Selection Approaches in Decomposition-based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization
2022
In offline data-driven multiobjective optimization, no new data is available during the optimization process. Approximation models, also known as surrogates, are built using the provided offline data. A multiobjective evolutionary algorithm can be utilized to find solutions by using these surrogates. The accuracy of the approximated solutions depends on the surrogates and approximations typically involve uncertainties. In this paper, we propose probabilistic selection approaches that utilize the uncertainty information of the Kriging models (as surrogates) to improve the solution process in offline data-driven multiobjective optimization. These approaches are designed for decomposition-base…
A mathematical approach to predict the solids concentration in anaerobic membrane bioreactos (AnMBR): Evaluation of the volatile solids solubilization
2020
[EN] Anaerobic Membrane Bioreactors (AnMBR) are gaining attention as a suitable approach for sustainable low-strength wastewater treatment, as they bring together the advantages of both anaerobic treatments and membrane bioreactors. However, increasing the sludge retention time (SRT) necessary to favor hydrolysis increases the suspended solids concentration potentially leading to decreased permeate flux. Therefore, the availability of a mathematical approach to predict the solids concentration within an AnMBR can be very useful. In this work, a mathematical model describing the volatile solids concentration within the reactor as a function of the operating parameters and the influent charac…
Transportation-cost inequality on path spaces with uniform distance
2008
Abstract Let M be a complete Riemannian manifold and μ the distribution of the diffusion process generated by 1 2 ( Δ + Z ) where Z is a C 1 -vector field. When Ric − ∇ Z is bounded below and Z has, for instance, linear growth, the transportation-cost inequality with respect to the uniform distance is established for μ on the path space over M . A simple example is given to show the optimality of the condition.
Isolation and Characterization of CD276+/HLA-E+ Human Subendocardial Mesenchymal Stem Cells from Chronic Heart Failure Patients: Analysis of Differen…
2012
Mesenchymal stem cells (MSCs) are virtually present in all postnatal organs as well as in perinatal tissues. MSCs can be differentiated toward several mature cytotypes and interestingly hold potentially relevant immunomodulatory features. Myocardial infarction results in severe tissue damage, cardiomyocyte loss, and eventually heart failure. Cellular cardiomyoplasty represents a promising approach for myocardial repair. Clinical trials using MSCs are underway for a number of heart diseases, even if their outcomes are hampered by low long-term improvements and the possible presence of complications related to cellular therapy administration. Therefore, elucidating the presence and role of MS…
Hepatitis C virus prevalence and level of intervention required to achieve the WHO targets for elimination in the European Union by 2030: a modelling…
2017
Background Hepatitis C virus (HCV) is a leading cause of liver-related morbidity and mortality worldwide. In the European Union (EU), treatment and cure of HCV with direct-acting antiviral therapies began in 2014. WHO targets are to achieve a 65% reduction in liver-related deaths, a 90% reduction of new viral hepatitis infections, and 90% of patients with viral hepatitis infections being diagnosed by 2030. This study assessed the prevalence of HCV in the EU and the level of intervention required to achieve WHO targets for HCV elimination. Methods We populated country Markov models for the 28 EU countries through a literature search of PubMed and Embase between Jan 1, 2000, and March 31, 201…
PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches
2019
Geospatial computation, data transformation to a relevant statistical software, and step-wise quantitative performance assessment can be cumbersome, especially when considering that the entire modelling procedure is repeatedly interrupted by several input/output steps, and the self-consistency and self-adaptive response to the modelled data and the features therein are lost while handling the data from different kinds of working environments. To date, an automated and a comprehensive validation system, which includes both the cutoff-dependent and –independent evaluation criteria for spatial modelling approaches, has not yet been developed for GIS based methodologies. This study, for the fir…
Determinants of performance drivers in online food delivery platforms: a dynamic performance management perspective
2022
PurposeThis study aims to demonstrate that the Dynamic Performance Management (DPM) framework, integrating performance management with system dynamics modelling, enables decision-makers to identify sustainable strategies in online food delivery platforms, thereby avoiding company failure.Design/methodology/approachThis study undertakes a multistep methodological approach. After the literature review, a retrospective case study approach was used. To build the DPM framework and the system dynamics simulation model, primary and secondary data were collected and analysed.FindingsThis study by adopting the DPM perspective highlights the critical role performance drivers play to assess the viabil…
Supporting the natural gas supply chain public policies through simulation methods: A dynamic performance management approach
2018
Natural gas is considered the transitional fuel par excellence between fossil and renewable sources, considering its low cost, greater efficiency and lesser impact on the environment. This is the reason why its demand levels have increased worldwide, requiring intervention of public and private stakeholders in order to meet these increments. The participation of diverse interconnected stakeholders (key actors) of the supplier-client form, constitutes a supply chain for natural gas, in which the effects of the application of public policy actions can be analysed in the time, using Dynamic Performance Management DPM methodology. The results of the model show the behaviour of the reserves, pro…