Predicting air pollution is an important prerequisite for estimating, monitoring and mapping unknown pollution values. We can use fuzzy spatial prediction techniques to determine pollution concentration areas in practical situations where our observations are imprecise and vague. Fuzzy membership kriging with a semi-statistical membership function is an example of this type of technique. The im...

    In this research in order to frequency analysis of maximum daily rainfall in various climates of Iran the data of 40 synoptic rain gauges collected in 40 years period i.e., 1973 to 2012 were used. These stations are located in various climates of Iran according to De Martonne climatic classification. At first, input of data to HYFA package was performed. The mentioned package includes seven...

Fiber lengths were analyzed for random samples of medium-density fiberboard (MDF) fibers and wood particles taken from eleven different populations. For six of the samples, the lognormal distribution fit the data, while the Weibull distribution did not. For three of the samples, the Weibull fit the data, while the lognormal did not. For two of the samples, both the lognormal and Weibull fit the...

drought monitoring is a fundamental component of drought risk management. it is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolation of spatially referenced data and the prediction of values...

In previous work on unsupervised learning of morphology, the long-tail pattern in the rank-frequency distribution of words, as well as of morphological units, is usually considered as following Zipf’s law (power-law). We argue that these long-tail distributions can also be considered as lognormal. Since we know the conjugate prior distribution for a lognormal likelihood, we propose to generate ...

Recently, commentators have suggested that the distributional form of cost data should be explicitly modelled to gain efficiency in estimating the population mean. We perform a series of simulation experiments to evaluate the usual sample mean and the mean estimator of a lognormal distribution, in the context of both theoretical distributions and three large empirical datasets. The sample mean ...

Many data arising in reliability engineering can be modeled by a lognormal distribution. Empirical evidences from many sources support this argument. However, sometimes the lognormal distribution does not completely satisfy the fitting expectations in real situations. This fact motivates the use of a more flexible family of distributions with both heavier and lighter tails compared to the logno...

This paper proposes an efficient and accurate non-intrusive uncertainty quantification (UQ) method in computational fluid dynamics (CFD). Emphasis is placed on developing an UQ method that can accurately predict stochastic behaviors of output solution with small number of sampling simulations, and is also accurate for non-smooth output uncertainty responses. The proposed method is based on Krig...

Genomic data provide a valuable source of information for modeling covariance structures, allowing a more accurate prediction of total genetic values (GVs). We apply the kriging concept, originally developed in the geostatistical context for predictions in the low-dimensional space, to the high-dimensional space spanned by genomic single nucleotide polymorphism (SNP) vectors and study its prope...

We present Top-kriging, or topological kriging, as a method for estimating streamflow-related variables in ungauged catchments. It takes both the area and the nested nature of catchments into account. The main appeal of the method is that it is a best linear unbiased estimator (BLUE) adapted for the case of stream networks without any additional assumptions. The concept is built on the work of ...