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Fuzzy neural network model and intelligent prediction method for deep excavation deformation

A technology of fuzzy neural network and deep foundation pit, applied in the field of fuzzy neural network model, which can solve the problems of high engineering accidents and great harm.

Inactive Publication Date: 2013-05-22
SUZHOU UNIV OF SCI & TECH
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Problems solved by technology

Since the construction of deep foundation pit engineering cannot get rid of the influence of many factors such as space, time, natural environment, and man-made, the probability of engineering accidents is still high and the hazards are relatively high.

Method used

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  • Fuzzy neural network model and intelligent prediction method for deep excavation deformation
  • Fuzzy neural network model and intelligent prediction method for deep excavation deformation
  • Fuzzy neural network model and intelligent prediction method for deep excavation deformation

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Embodiment Construction

[0045] The method for intelligently predicting the deformation of a deep foundation pit in this embodiment includes the following five steps:

[0046] Step 1: Select the main influencing factors of the dynamic change of foundation pit deformation.

[0047] There are many factors affecting the deformation of the foundation pit, which mainly include the excavation depth D, the groundwater level W, the depth of the measuring point H1, the stiffness of the pile EI, the depth of the pile into the soil H2, and the cohesion of the soil above the excavation surface of the foundation pit. Weighted average The weighted average value of the internal friction angle of the soil above the excavation surface of the foundation pit The weighted average of the weight of the soil above the excavation surface of the foundation pit The weighted average of the cohesion of the soil below the excavation face of the foundation pit The weighted average value of the internal friction angle of the...

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Abstract

The invention discloses a fuzzy neural network model based on a multivariable phase-space reconstruction theory and an intelligent prediction method for deep excavation deformation by using the fuzzy neural network model. The fuzzy neural network model consists of four functional modules including a fuzzification interface, a fuzzy rule knowledge base, a fuzzy inference machine and a defuzzification device. The prediction model and the prediction method have high accuracy, and can effectively avoid major losses of countries and people's lives and properties.

Description

technical field [0001] The invention relates to a fuzzy neural network model based on multivariable phase space reconstruction and a method for intelligently predicting deformation of deep foundation pits by using the fuzzy neural network model. Background technique [0002] Since the 1990s, the rapid development of national infrastructure construction and urban high-rise housing construction has led to the stability of the excavation of deep foundation pits and the monitoring of environmental effects have become increasingly concerned issues. Since the construction of deep foundation pit engineering cannot get rid of the influence of many factors such as space, time, natural environment, and man-made, the probability of engineering accidents is still high and the hazards are relatively large. [0003] There are many factors that affect the deformation of deep foundation pits, which are interrelated and restrict each other, such as excavation depth, soil layer distribution a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N7/02
Inventor 奚雪峰班建民陆卫忠付保川
Owner SUZHOU UNIV OF SCI & TECH
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