Computer experiments are becoming increasingly popular in studying complex real world systems. A special class of sliced Latin hypercube design is proposed in this paper. Such designs are particularly suitable for computer experiments with both qualitative and quantitative factors, multi-fidelity computer experiments, cross-validation and data pooling. The resulting sliced Latin hypercube desig...

We investigate minimax Latin hypercube designs in two dimensions for several distance measures. For the `-distance we are able to construct minimax Latin hypercube designs of n points, and to determine the minimal covering radius, for all n. For the `1-distance we have a lower bound for the covering radius, and a construction of minimax Latin hypercube designs for (infinitely) many values of n....

In this paper we review several uncertainty and sensitivity methods available in the literature and provide recommendations for implementing some of these methods in Ecolego. Predictive models used in the assessment of protection of the environment from ionising radiation present some extreme characteristics that make uncertainty and sensitivity analysis a non-trivial task. Those characteristic...

In the past few years, construction of multi-storey timber buildings has increased significantly in locations where high-intensity ground motions are likely to occur. On other hand, fast development wood engineered products, as glued-laminated (GLT) and cross-laminated (CLT), been challenging researchers provide adequate guidelines for design assessment structures built seismic regions. Some an...

In the area of computer simulation Latin hypercube designs play an important role. In this paper the class of maximin Latin hypercube designs is considered. Up to now only several two-dimensional designs and designs for some small number of points are known for this class. Using periodic designs and simulated annealing we extend the known results and construct approximate maximin Latin hypercub...

A new procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a systematic employment of stochastic sensitivity analysis and a genetic algorithmbased training of a neural network by an evolutionary algorithm...

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas—contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampl...

This note provides a description of a procedure that is designed to efficiently optimize expensive black-box functions. It uses the response surface methodology by incorporating radial basis functions as the response model. A simple method based on a Latin hypercube is used for initial sampling. A modified version of CORS algorithm with space rescaling is used for the subsequent sampling. The p...