Slope displacement fractal forecasting method improved by grey theory

Abstract

The invention discloses a slope displacement fractal forecasting method improved by a grey theory and relates to the high slope deformation forecasting field of strip mine. The slope displacement fractal forecasting method improved by the grey theory includes that using a grey model (1, 1) to carry out fitting prediction on a fractal dimension sequence according to a fractal theory and a grey forecasting theory to obtain fractal dimensions of next few periods, and using an inversion extrapolation method to inversely calculate the forecast fractal dimensions to obtain a precise slope deformation forecast value. The slope displacement fractal forecasting method improved by the grey theory is suitable for forecasting the high slope deformation of the strip mine and capable of effectively solving the problems of low high mine slope deformation forecasting precision and bad forecasting stability of the traditional fractal forecasting under the condition of small sample monitored data with volatility, and accordingly the forecasting error range is controlled effectively, the reliance of a forecasting model on large quantity of monitored data is reduced, and the practicability of the fractal forecasting is improved in application.

Description

technical field [0001] The invention relates to the technical field of geotechnical engineering, in particular to the fields of large-scale open-pit mine mining and high-side slope treatment in open-pit mines, and in particular to a method for predicting deformation of high-side slopes in open-pit mines. Background technique [0002] Slope stability prediction and analysis have been paid more and more attention by people, especially in recent years with the rapid development of mining projects, some open-pit mines have generally entered the late stage of deep mining, and large-scale high slopes have appeared more in open-pit mines ; This not only affects the normal mining of mines, but also poses a serious threat to people's lives and properties. The existing slope deformation monitoring methods mainly rely on instruments such as total stations, levels, and rangefinders to collect data on slope displacement; however, these instruments and equipment only obtain the past defor...

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Problems solved by technology

[0004] At present, according to the existing literature statistics, although different prediction models have been used in the prediction of slope deformation, their poor fit for nonlinear data and the requirement for large amount of data severely limit the application of prediction models; Moreover, in practice, due to the limitations of the natural environment or equipment conditions, we often obtain small samples, data sequences with obvious nonlinear and volatility characteristics

Under this condition, although the fractal model has a good fit to the nonlinear data sequence, under the condition of small sample data sequence, the traditional fractal model also has low prediction accuracy, poor prediction stability and susceptibility to environmental factors. Defects such as interference

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