Journal:Informatica
Volume 19, Issue 1 (2008), pp. 63–80
Abstract
This paper presents the application of multi-criterion approach to the analysis and comparison of reference alternatives of wind power park information system (WPPIS) which complies with the standard IEC 61400-25. The comparison is based on multi-criterion preferences measured in domination rate (index). The reference alternatives include centralized, mixed and seamless communication topologies. The major features of these alternatives are discussed as well as the multi-criterion methodology applied covering pair comparison, Pareto sets and fuzzy sets methods. The current investigation described is an extension of the preceding investigation of the same reference alternatives of WPPIS. As we have showed, the transition from the concerted experts view as it was a case in previous investigation to the conflicting expert views in the current investigation proved the high robustness of solution made for the case of concerted expert views: the rank of preferences for alternatives remained the same, with seamless communication topology on the top the rank.
Journal:Informatica
Volume 2, Issue 4 (1991), pp. 564–578
Abstract
The present paper considers a constant-parameter estimation algorithm for an analog transfer function by discrete observations of the object's input and output variables. The algorithm is based on supplementary variables and least-squares methods. It is assumed, that the order of the transfer function is known and the derivatives of the input and output variables are non-measurable. The supplementary variables and their derivatives are constructed from discrete observations of the input and output variables by applying a numerically realized analog filter. Investigation results for the estimate properties are presented. The results were obtained by the method of statistical simulation.
Journal:Informatica
Volume 1, Issue 2 (1990), pp. 87–95
Abstract
The present paper considers the problem of general estimation of static model parameters and systematic measurement errors. The general estimation algorithm is based on static model linearization and on the least-squares method. The efficiency of this algorithm is illustrated by means of computer-aided digital simulation. The obtained equations and the algorithm of general estimation of static model parameters and systematic measurement errors can be applied for the solution of different practical problems. Estimatibility conditions must be satisfied in all cases.