Optimum design of structures is achieved while the design variables are continuous and discrete. To reduce the computational work involved in the optimization process, all the functions that are expensive to evaluate, are approximated. To approximate these functions, a semi quadratic function is employed. Only the diagonal terms of the Hessian matrix are used and these elements are estimated fr...

This paper proposes a triangulation method for a digitized surface whose points are located on a regular lattice. The method relies on an iterative and adaptive splitting of triangular faces of an initial polyhedral surface. Assuming a bijection between the digitized surface and its approximation, a partition of the data base is performed. The method allows the measurement of the local quality ...

Introduction Multivariate Fay–Herriot models for estimating small area indicators are introduced. Among the available procedures for fitting linear mixed models, the residual maximum likelihood (REML) is employed. The empirical best predictor (EBLUP) of the vector of area means is derived. An approximation to the matrix of mean squared crossed prediction errors (MSE) is given and four MSE estim...

D Second test: complex forms: velocity prediction 27 D.1 Data recording and approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 D.2 Curvature and velocity computations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 D.3 Geometrically combined velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 D.4 Expanded results . . . . . . . ....

Prediction of future values of a shot noise process observed on a discrete lattice of points is considered. The shot magnitudes are assumed to be independent and identically distributed and arrive via a Poisson process; the eeect of each shot dissipates and/or accumulates according to a known shot function. Conditional mean and linear point predictors of future process values are developed. Dis...

We consider the problem of minimizing expected prediction cost, when there are costs associated with determining attribute values. Given a Boolean hypothesis function and a sample of this function, we seek to minimize the average prediction cost over the sample (Sample-BFE problem). We define and explore two different versions of this problem and show how existing work can be used to yield appr...

We evaluate different prediction techniques to estimate future demand of resource usage in a computational market. Usage traces from the PlanetLab network are used to compare the prediction accuracy of models based on histograms, normal distribution approximation, maximum entropy, and autoregression theory. We particularly study the ability to predict the tail of the probability distribution in...

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it is firstly proved that the multi-input-single-output (miso) fuzzy systems based on interval-valued $r$- and $s$-implications can approximate any continuous function defined on a compact set to arbitrary accuracy.  a formula to compute the lower upper bounds on the number  of interval-valued fuzzy sets needed to achieve a pre-specified approximation  accuracy for an arbitrary multivariate con...

the specific heat of cd mn se (x = 0.01) and cd , mn s (x = 0.026) in the temperature range of 0.3 - 40k was measured. the measurements were carried out in different applied magnetic fields (h = 0,10,20, 28kg). the results were analyzed with a model which includes long range interactions. calculations based on on extended version of nearest neighbor pair approximation (including triplets) yield...