This paper introduces and analyzes the application of the least square method and Kalman filter in time prediction.

Following a brief review of the research course and a further definitio n and discussion of some concepts of time prediction of landslide,the paper poin ts out problems in the present time prediction of landslides and advances fundam ental ideas and technical courses of GMD model for landslide prediction based on the author s years of research.

ased on the introduction to the geological characteristics and classification of accumulational ladslide,the anthors present the main effect factors of slope stability,discuss the relationberwwen the stability analysis and the time forecast of landslide.

At present,the temporal prediction of landslide activity are difficult problems of landslide research,it develops slowly.

The experiments of ship rolling time series prediction are done on the ground of the time series analysis.

The experiments of ship rolling time series prediction are done using the error back propagation neural network, the results performed well.

Combining wavelet analysis and neural network characteristics, the error back propagation wavelet neural network based structure and algorithm to ship roll time series prediction are given .

Analysis of length of predictable time of chaotic time series;

Annealing cooling processes are classified in accordance with material and thickness of each steel coil in annealing plan,then multi-input and single-output modeling problem for cooling time prediction of hood-type annealing furnace is simplified to a group of single-input and single-output modeling problem.