Prediction method of monitoring displacement based on correlation coefficient stationary series with unequally spaced data

An analysis method of unequally spaced correlation coefficient stationary series was established, which can be used into model buildings and prediction of displacement monitoring in geotechnical and hydraulic engineering. The integral maximum likelihood estimations of model parameters were derived from stochastic process theory; it can not only guarantee the good statistical properties but also solve the problem of unequally spaced time series analysis. Traditional interpolation method will result in an unacceptable error when the rate of data missing was relatively high, which was proved by the Monte Carlo simulation. It is shown that the estimations of the variance of displacement series are far from the true value. An example was given in the last section, which illustrates the advantage of presented method.