Robust control based on an online estimation of uncertainty is presented for a class of nonlinear uncertain systems. The estimation is done via a robust observer after the uncertainty vector is projected onto a one-dimensional subspace. The proposed combination of dynamics projection and online estimation is to relax the knowledge about the size of uncertainty and required in the robust control...

Population variability and uncertainty are important features of biological systems that must be considered when developing mathematical models for these systems. In this paper we present probability-based parameter estimation methods that account for such variability and uncertainty. Theoretical results that establish well-posedness and stability for these methods are discussed. A probabilisti...

Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between scales and variable statistics. It is extended with two different uncertainty propagation method...

making capital and investment is the main driving forces of economic development. based on the investment sensitivity to the changes of some of macro-economic variables and risk and uncertainty, the present study evaluated the effective factors on investment in private sector in iran during 1980-2007. at first, the uncertainty variables of real informal exchange rate, nominal interest rate and ...

Software effort estimation is one of the most critical and complex, but an inevitable activity that takes place during the early stages of SDLC. Software size estimate is one of the most popular inputs for software effort prediction models. Providing a good size estimate for the purpose of accurately estimating the development effort is a challenging problem. During estimation activities, the u...

Fundamental matrix estimation is difficult since it is often based on correspondences that are spoilt by noise and outliers. Outliers must be thrown out via robust statistics, and noise gives uncertainty. In this article we provide a closed-form formula for the uncertainty of the so-called 8 point algorithm, which is a basic tool for fundamental matrix estimation via robust methods. As an appli...

Recent studies have shown that Bayesian Neural Networks (BNNs) are powerful tools for providing reliable hydrologic prediction and quantifying the prediction uncertainty. The reasonable estimation of the prediction uncertainty, a valuable for decision making to address water resources management and design problems, is influenced by the techniques used to deal with different uncertainty sources...

Although the Eurachem guide shows some examples, analytical chemists frequently have regarded the estimation of uncertainty as too theoretical and not suitable for the estimation of uncertainties of complex chemical techniques. This is because identifying and quantifying all sources of uncertainty is difficult and laborious, for procedures consisting of numerous steps, many of which are not alw...

Software project development process is requiring accurate software cost and schedule estimation for achieve goal or success. A lot it referred to as the ―Intricate brainteaser‖ because of its conscience attribute which is impact by complexity and uncertainty, Generally estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward—once you...

Software project development process is requiring accurate software cost and schedule estimation for achieve goal or success. A lot it referred to as the “Intricate brainteaser” because of its conscience attribute which is impact by complexity and uncertainty, Generally estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward—once you...