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Developed economies depend on complex and extensive systems of infrastructure to maintain economic prosperity and quality of life. In recent years, the implementation of Structural health monitoring (SHM) systems on full-scale bridges has increased. The go ...
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...
Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...
This paper reports a method for the simultaneous estimation of unwrapped phase and higher order phase derivatives from a single phase fringe pattern recorded in an optical interferometric setup, thereby overcoming substantial barriers to achieving such mea ...
This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that contr ...
Compared to daily rainfall data, observed subdaily rainfall times are rare and often very short. For hydrologic modeling, this problem is often addressed by generating synthetic hourly rainfall series, with rainfall generators calibrated on relevant rainfa ...
Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incur ...
Structural health monitoring (SHM) has the potential to provide quantitative and reliable data on the real condition of structures, observe the evolution of their behaviour and detect degradation This paper presents two methodologies for model-free data in ...
In this thesis, we treat robust estimation for the parameters of the Ornstein–Uhlenbeck process, which are the mean, the variance, and the friction. We start by considering classical maximum likelihood estimation. For the simulation study, where we also in ...
Diffusion adaptive networks tasked with solving estimation problems have attracted attention in recent years due to their reliability, scalability, resource efficiency, and resilience to node and link failure. Diffusion adaptation strategies that are based ...
