Abstract
Enhancing the validity of methodical recommendations is one of the main problems that have to be solved in developing intelligent systems for managing maintenance and repair of electric power system equipment and devices. A risk of making an erroneous decision exists mainly due to availability of gross errors and abnormal values in statistical data on operation. The difficulty of solving this problem becomes still more obvious obvious if this risk is taken together with the fact that non-random samples of statistical data on operation differ from the theoretical representative samples of random quantities from the general totality of data, the need to consider a multidimensional nature of statistical data on operation, and lack of methods for analyzing scanty samples of multidimensional data. A method that allows abnormal realizations to be revealed based on the fiducial approach and statistical hypothesis testing theory is developed. By applying express methods for calculating the fiducial interval critical values for the selected significance level, this problem can be solved without using special tables and a computer.
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