Simulation output is generally stochastic and autocorrelated, and includes the initial condition bias. To exclude the bias, the determination of truncation point has been one of important issues for the steady-state simulation output analysis. In this paper, two methods are presented for detection of truncation point in order to estimate efficiently the steady-state measure of simulation output. They are based on the Euclidean distance equation, and the backpropagation algorithm in Neural Networks. The experimental results obtained by M/M/1 and M/M/2 show that the proposed methods are very promising with respect to coverage and relative bias. The methods could be used for the on-line analysis of simulation outputs.