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Construction engineering project risk prediction method based on one-dimensional convolutional neural network

A convolutional neural network and construction engineering technology, applied in the field of risk prediction of construction projects based on one-dimensional convolutional neural network, can solve the problem of low risk prediction accuracy, and achieve more convincing and reliable prediction results. , high precision effect

Pending Publication Date: 2020-09-15
SOUTHWEST PETROLEUM UNIV
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  • Application Information

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Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, a construction project risk prediction method based on a one-dimensional convolutional neural network provided by the present invention solves the problem of low accuracy of traditional construction project risk prediction

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  • Construction engineering project risk prediction method based on one-dimensional convolutional neural network
  • Construction engineering project risk prediction method based on one-dimensional convolutional neural network
  • Construction engineering project risk prediction method based on one-dimensional convolutional neural network

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[0058] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0059] like figure 1 As shown, the present invention provides a method for predicting the risk of a construction project based on a one-dimensional convolutional neural network, and its implementation method is as follows:

[0060] S1. Identify the risks of construction projects and build a risk evaluation index system; the implementation method is as follows:

[0061] S101. Identify the risks of the construction project; ...

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Abstract

The invention provides a constructional engineering project risk prediction method based on a one-dimensional convolutional neural network. Firstly, risks existing in a constructional engineering project are recognized, and a risk evaluation index system is constructed; a risk value of each risk evaluation index is determined; a one-dimensional convolutional neural network model is constructed totrain and learn the risk value of the constructional engineering project, the construction period risk is selected in the constructional engineering project as an output unit of the convolutional neural network, and the risk of the engineering project is predicted by analyzing the average absolute error value of the predicted value and the actual value of the construction period risk. According tothe invention, the problem of low risk prediction accuracy of a traditional constructional engineering project is solved.

Description

technical field [0001] The invention belongs to the technical field of construction engineering, and in particular relates to a method for predicting the risk of a construction project based on a one-dimensional convolutional neural network. Background technique [0002] With the continuous development of science and technology, the complexity of construction projects continues to increase, the construction cycle continues to grow, and there are many uncertain factors. In order to reduce the probability of risk occurrence and effectively avoid the loss of potential risks to the entire project, there are It is necessary to predict the risks of construction projects. Existing literature proposes to analyze the risk relationship of power grid construction projects based on rough set theory, and calculate the correlation coefficient of risk factors to provide a basis for project risk management, but there is a problem that the correlation between two project risk factors is not ...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/08G06N3/04G06N3/08
CPCG06Q10/0635G06Q50/08G06N3/084G06N3/045
Inventor 钟亚雯陈蕾蕾胡榉丹
Owner SOUTHWEST PETROLEUM UNIV