Grey Prediction Research of Slope Deformation

 

Yanmei Yang

Associate Professor, School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu, China
e-mail: xinanyym@163.com

Zegen Wang

Professor, School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu, China
e-mail: zegen01@126.com

 

 ABSTRACT

After introducing the basic theories related to grey system such as grey information, gray generation series, grey correlation analysis, the author unfolds a discussion on data transform method of gray mathematics sequence and general grey prediction mode in deformation forecast. Thus, Metabolism forecast model is suggested to be adopted in deformation observation of the forecast analysis considering the influence of general grey prediction mode on the process as well as the result when operating on the relationship between the new and the original information. Taking one of the slope deformation observation data as an example, the author carries some exclusive studies on general grey forecasting, new information grey forecasting and metabolism grey forecasting. Compared with the results predicted by general grey forecasting and new information grey forecasting, metabolism grey forecasting enjoys the minimum residual mistakes of slope deformation, being the top conformable to the actual measured data and the weakest relative errors-maker. It is thus clear that metabolism grey forecasting is the best choice for slope deformation forecast. Moreover, problems like heavy data, high computing cost and low efficiency led by prolonged periodic time in observing can also be avoided with metabolism grey forecasting.

Keywords: Grey system, grey model, data transform, deformation forecast, grey forecasting model

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