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Deep foundation pit deformation prediction method and system based on neural network and rough set classification

A neural network and prediction method technology, applied in the field of deep foundation pit deformation prediction, can solve the problems of not considering the optimal value of the penalty factor C input parameters, weak generalization ability, etc., to achieve strong self-learning ability, good prediction and early warning ability , the effect of improving the accuracy

Inactive Publication Date: 2020-09-25
BEIJING DACHENG GUOCE TECH
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Problems solved by technology

However, the prediction model does not consider the optimal value of the penalty factor C and the input parameters affecting the deformation of the foundation pit, which makes the generalization ability of the model weak when dealing with changes in working conditions

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  • Deep foundation pit deformation prediction method and system based on neural network and rough set classification
  • Deep foundation pit deformation prediction method and system based on neural network and rough set classification
  • Deep foundation pit deformation prediction method and system based on neural network and rough set classification

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[0042] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.

[0043] The technical scheme of the present invention will be described in detail below in conjunction with the accompanying drawings. According to one embodiment of the present invention, a deep foundation pit deformation prediction method based on neural network and rough set classification is provided. figure 2 The flow chart of the deep foundation pit deformation prediction method based on neural network and rough set...

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Abstract

The invention relates to a deep foundation pit deformation prediction method and system based on a neural network and rough set classification. Quantitative analysis can be carried out by utilizing arough set theory, so that the characteristics of the relationship between the data are reasoned and explained, a large number of index attributes influencing deep foundation pit deformation are reduced, the input dimension of a neural network is reduced, and the reduced index attributes are input into the neural network for prediction, so that the efficiency and accuracy of deep foundation pit risk prediction are improved.

Description

technical field [0001] The invention relates to the related field of foundation pit settlement monitoring technology, in particular to a deep foundation pit deformation prediction method and system based on neural network and rough set classification. Background technique [0002] In the process of accelerated development of urban construction, due to the limitation of surface space, more and more buildings are developed to be super high and underground, so a large number of deep foundation pit projects have appeared. Due to complex factors such as geological conditions, hydrological conditions, construction technology and surrounding environment, during the excavation of deep foundation pits, in order to ensure the dryness and safety of the site, it is usually necessary to reduce the groundwater level below the excavation surface through precipitation. Changes in groundwater seepage field, deformation of surrounding soil, ground subsidence, and deformation of foundation pit...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/08G06N3/08
CPCG06N3/08G06Q10/04G06Q50/08
Inventor 蒋梦张怀王鹤康秋静高占建高飞董建华丁海友
Owner BEIJING DACHENG GUOCE TECH
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