A.E. Tercan

Importance of Orthogonalization Algorithm in Modeling Conditional Distributions by Orthogonal Transformed Indicator Methods

The orthogonal transformed indicator approach to conditional cumulative distribution functions is based on the decomposition of the indicator variogram matrix as a matrix product. This paper explores the manner in which the decomposition algorithm affects the conditional cumulative distribution function as estimated by orthogonal transformed indicator kriging. Five decomposition algorithms are considered: spectral, Cholesky, symmetric, Cholesky-spectral, and simultaneous decompositions. Impact of the algorithms on spatial orthogonality and order relations problems is examined and their performances together with indicator kriging are compared using a real dataset.

Approximate local confidence intervals under change of support

Approximate local confidence intervals are constructed from uncertainty models in the form of the conditional distribution of the random variable Z given values of variables [Zi, i=1,...,n]. When the support of the variable Z is any support other than that of the data, the conditional distributions require a change of support correction. This paper investigates the effect of change of support on the approximate local confidence intervals constructed by cumulative indicator kriging, class indicator kriging, and probability kriging under a variety of conditions. The conditions are generated by three simulated deposits with grade distributions of successively higher degree of skewness; a point support and two different block supports are considered. The paper also compares the confidence intervals obtained from these methods using the most used measures of confidence interval effectiveness.

Assessment of Surface Quality of Stone Treated by Water Jet and Bush Hammering Using Geostatistical Simulations

A number of surface-treatment methods can be used to increase the rock roughness to improve its antislip properties while preserving aesthetic appearance. Bush hammering and water jetting are two of these surface-treatment methods. In this study, Sardinian basalt samples were treated with plain water jet and soft and hard bush-hammering methods, and quality of surfaces treated was assessed geostatistically. Realizations of the treated surfaces were generated by using sequential Gaussian simulation. The results show that the surfaces treated by the water-jet method are more homogeneous than others.

Estimation of trona grade by fuzzy modelling

The estimation of reserves is directly related to the financial investments. In this study, fuzzy approach was presented for estimating ore grades which is the main part of reserve estimation. Data driven fuzzy modelling technique is applied to estimate the grades in a trona (natural soda) deposit. Performance evaluations of the fuzzy model showed that fuzzy modelling is a useful tool for the estimation of ore parameters

Bootstrap estimation of the daily mean pick consumption in mechanical excavation

Abstract The aim of this study was to set confidence intervals for the daily mean pick consumption which is a useful parameter in designing a longwall panel and also deciding the critical storage level of new picks. For this purpose, the bootstrap is introduced and the method is applied to the daily mean pick consumption data recorded at the longwall panels of the Cayirhan lignite field, Ankara. Serial correlation for the data was tested by means of the experimental variograms. Finally, 95% confidence intervals for the daily mean consumption were constructed from sampling distributions obtained by bootstrapping. The results show that the upper seam leads to higher pick consumption and wider confidence intervals than the lower seam.