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This paper presents a multivariate UPD estimator, family member [A,U,T] with parameters p and s, which allows to calculate simultaneously parameters of Weibull K and C at a point Pe from the measured values of these variables in several sampling points. During the 3D estimation, the spatial relationship between the data and the associated values of elevation and roughness of the terrain is taken into account; with the estimated results, a model of wind energy resources is developed, given by a 3D mesh where to each node is associated the values of K and C. Finally, a method of combinatory optimization is described to find the values of p and s such that the mesh model is feasible and optimal for the given data. [ABSTRACT FROM AUTHOR]

The potential field inverse problems are difficult to solve by means of automatic methods, one major reason for this is the inability of conventional procedures to locate the globally optimal set of parameters. This paper establish clearly the nature of the multiple optima problem for the research to inversion of potential field data in the six parameters model and investigates the consistency with three global optimization methods. The Multistart Simplex (MSX) method, a Genetic algorithm combined with Simplex (GSX) and the Shuffled Complex Evolution (SCE) method. All of them are able to find the optimal parameters set during the inversion of potential field data for a six-parameter model. In 100 independent trials of each algorithm the SCE procedure appears to be about 3 times more efficient than MSX procedure and twice time more efficient than GSX. The GSX procedure appears to be about 2 times more efficient than MSX. [ABSTRACT FROM AUTHOR]