In this study, optimum combinations of available rainfall gauging stations are selected by a model which is consist of geo statistics model as an estimator  and an optimized model. At the  first,  watershed  is  approximated  to  several  regular  geometric  shapes.  Then  kriging calculates  the  variance &nbs...

We examine a certain class of nonstationary inverse problems. We view them as a state estimation problem. The time evolution of the state of the system is modeled by a stochastic differential equation. The observation equation is linear with additive measurement noise. We introduce the time discrete infinite dimensional state estimation system concerning the problem. For computational reasons t...

State estimation is essential to access observable network models for online monitoring and analyzing of power systems. Due to the integration of distributed energy resources and new technologies, state estimation in distribution systems would be necessary. However, accurate input data are essential for an accurate estimation along with knowledge on the possible correlation between the real and...

In parameter estimation, assumptions about the model are typically considered which allow us to build optimal estimation methods under many statistical senses. However, it is usually the case where such models are inaccurately known or not capturing the complexity of the observed phenomenon. A natural question arises to whether we can find fundamental estimation bounds under model mismatches. T...

ABSTRACT Estimation of mineral resources and reserves with low values of error is essential in mineral exploration. The aim of this study is to estimate and model a vein type deposit using disjunctive kriging method. Disjunctive Kriging (DK) as an appropriate nonlinear estimation method has been used for estimation of Cu values. For estimation of Cu values and modelling of the distributio...