ABSTRACT
ABSTRACT Point estimate method (PEM) is an efficient approach for stochastic system analysis. For most of PEMs, however, the precision depends on the number of nodes which is always determined subjectively and empirically. In this work, two PEMs are proposed. One is the direct iterative point estimate method (DIPEM), where the moment is calculated with increasing number of nodes until the results converge. The other is the adaptive iterative point estimate method (AIPEM), in which the function nonlinearity can be calculated, thus the number of nodes is determined rationally and the moments are obtained. Several numerical cases are analyzed to verify the proposed methods. Results indicate that the efficiency of existing PEMs is the best, but the results may be inaccurate, especially for higher statistical moments. The precision of DIPEM and AIPEM are always high enough, and AIPEM is more efficient than DIPEM.
