Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill...

Cation exchange capacity (CEC) is one of the most important soil attributes which control some basic properties of soil such as acidity, water and nutrient retaining capacity. However, the measurement of cation exchange capacity in large areas is time consuming and requires high expenses. One way to save time and expenses is to use simple soil covariates and geostatistical methods in mapping CE...

The formal expression of pro positional attitudes, especially when nested (iterated), is an important problem for A I . An interesting first-order extensional logical system for such expression has been proposed by Creary. In this system concepts (and concepts of concepts, etc.) are made explicit. The system includes "concept functions", which are special functions which act on and deliver conc...

1. Abstract Over three decades, metamodeling has been widely applied to design optimization problems to build a surrogate model of computation-intensive engineering models. The Kriging method has gained significant interests for developing the surrogate model. However, traditional Kriging methods, including the ordinary Kriging and the universal Kriging, use fixed polynomials basis functions to...

An accurate estimation of soil organic matter (SOM) content for spatial non-point prediction is an important driving force for the agricultural carbon cycle and sustainable productivity. This study proposed a hybrid geostatistical method of extreme learning machine-ordinary kriging (ELMOK), to predict the spatial variability of the SOM content. To assess the feasibility of ELMOK, a case study w...

Maps are useful scientific tools for presenting environmental information, but the statistical techniques necessary to prepare scientifically rigorous maps have primarily focused on terrestrial habitats. This study compares three popular techniques (triangulation, kriging, and co-kriging) to map sediment grain size in Santa Monica Bay, California. Two grain size data sets, one collected in 1994...

The paper focuses on the fuzzy extensions of two data analysis methods, namely the fuzzy cluster analysis and the fuzzy interpolation of spatial data (the so-called fuzzy kriging) and their suitability for ecological applications. Both extensions utilize exact (crisp) measurement data as well as imprecise data defined as fuzzy numbers or fuzzy vectors. Fuzzy clustering of fuzzy data (conical fu...

Until now, Universal Kriging has not been used for the mapping of geological data in Croatia. However, it is one of the most frequently used methods of Kriging, probably the most adequate in cases when the input data is marked by a common trend. That exact feature is often an attribute of deep geological data, and thereby that of structural maps. Mapped surfaces in a row of examples have a stru...