Deep blasting failure area shape prediction method based on ADABOOST integration algorithm

Abstract

The invention discloses a deep blasting failure area shape prediction method based on an ADABOOST integration algorithm, and the method comprises the following steps: 1, collecting laboratory simulation real scene record data, carrying out the correlation analysis, and finding out main influence factors; 2, segmenting the data; 3, reprocessing the data; 4, segmenting the data; 5, training the data; 6, comparing the trained data with real data; and 7, evaluating a result. The invention belongs to the technical field of engineering blasting of metal mining, provides the deep blasting failure area shape prediction method based on the ADABOOST integration algorithm, and effectively solves the problems that in the prior art, blasting failure area shape prediction needs a large amount of development cost and needs a large amount of funds to purchase corresponding services, and the cost performance is low. The method shows that the machine learning method has practical reference value in the field of engineering blasting, the prediction result has theoretical significance, and the method is a prediction method capable of reducing development cost.

Description

technical field [0001] The invention belongs to the technical field of metal mining engineering blasting, in particular to a method for predicting the shape of a deep blasting damage zone based on an ADABOOST integrated algorithm. Background technique [0002] Energy has been an important factor for the survival of human beings for a long time. Due to the expansion of society's demand for energy and the increasingly scarce resources in the shallow part of the earth, the mining work of some ore bodies is gradually transitioning to the deep part of the earth. It has entered the state of deep resource mining one after another. In the past, the research on ore body blasting at home and abroad was mostly in the analysis stage using simulation software, so that the numerical simulation can calculate the velocity, strain, stress and energy field in the rock mass around the blast hole, which can Quantitatively describing the damage and flow state of rocks and then predicting the ran...

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Problems solved by technology

[0003] For above-mentioned situation, in order to overcome the defective of prior art, the object of the present invention is to provide a kind of deep blasting damage zone shape prediction method based on ADABOOST integration algorithm, effectively solve the need for a large amount of development cost and the need for blasting damage zone shape prediction in the past. A large amount of money is used to purchase corresponding services, and the problem of low cost performance is a predictive method to reduce development costs

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