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Memory, fire risk prediction model construction method, system and device

A technology of risk prediction and construction method, applied in prediction, instrument, character and pattern recognition, etc., can solve the problems of neglecting the nonlinear relationship of fire risk, low accuracy of prediction model, obvious collinearity and independence between independent variables, etc. Achieve effective development trend, collinearity and obvious effect of independence

Pending Publication Date: 2021-10-26
CHINA PETROLEUM & CHEM CORP +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] It only reflects the linear relationship between variables, ignoring the complex nonlinear relationship between fire risk in industrial parks and influencing factors, and the collinearity and independence between independent variables are obvious, resulting in low accuracy of the prediction model

Method used

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  • Memory, fire risk prediction model construction method, system and device
  • Memory, fire risk prediction model construction method, system and device
  • Memory, fire risk prediction model construction method, system and device

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Embodiment 1

[0057] In order to provide a more accurate model reference for predicting fire risks in industrial parks and developing more effective fire response and prevention measures, such as figure 1 As shown, a method for building a fire risk prediction model is provided in an embodiment of the present invention, comprising steps:

[0058] S11. Generate an independent variable data set according to the variable data set composed of variable items related to the fire occurrence in the target area; use the fire density in the target area as a dependent variable item and generate a dependent variable data set;

[0059] The target area in the embodiment of the present invention refers to the area where the fire risk of the industrial park is predicted; firstly, the influencing factors related to the occurrence of fire should be carried out within the target area as variable items, specifically, the variable items can include altitude , slope, aspect, normalized difference vegetation index...

Embodiment 2

[0093] In another aspect of the embodiment of the present invention, a device for constructing a fire risk prediction model is also provided, Figure 5 A schematic structural diagram of a fire risk prediction model construction device provided by an embodiment of the present invention is shown, and the fire risk prediction model construction device is compatible with figure 1 The device corresponding to the method for constructing the fire risk prediction model in the corresponding embodiment, that is, implemented in the form of a virtual device figure 1 In the method for building a fire risk prediction model in the corresponding embodiment, each virtual module constituting the apparatus for building a fire risk prediction model may be executed by an electronic device, such as a network device, a terminal device, or a server. Specifically, the fire risk prediction model construction device in the embodiment of the present invention includes:

[0094] The data acquisition unit...

Embodiment 3

[0101] On the basis of the second embodiment, the embodiment of the present invention may further include a ranking correction unit 05, which is used to judge the accuracy of the importance ranking of each variable factor according to the simple correlation coefficient between the predicted value and the actual value in the training set and the test set.

[0102] Similarly, the working principles and beneficial effects of the fire risk prediction model building device in the embodiment of the present invention have also been figure 1 The corresponding fire risk prediction model construction method is also recorded and explained, so it can be referred to each other, and will not be repeated here.

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Abstract

The invention discloses a memory, a fire risk prediction model construction method, system and device. The fire risk prediction model construction method comprises the following steps: forming a variable data set according to variable items related to fire occurrence of a target area and generating an independent variable data set; taking the fire density of the target area as a dependent variable item and generating a dependent variable data set; screening variable items in the variable data set through feature selection to obtain optimized variable items, and generating an importance degree sequence of the optimized variable items; determining a final variable item from the optimal variable items according to the importance degree sequence; forming a sample data set according to the final independent variable item and the dependent variable item; and randomly dividing a preset number of data subsets according to the sample data set, determining a training set and an internal test set from the data subsets, and generating a plurality of sub-models through training to construct a fire risk prediction model. According to the method, more accurate model reference can be provided for predicting the fire risk of the industrial park and developing more effective fire response prevention measures.

Description

technical field [0001] The invention relates to the field of process industry safety, in particular to a memory and a method, system and device for constructing a fire risk prediction model. Background technique [0002] The relatively dense buildings, crowds, and rich vegetation resources in the surrounding area have significantly increased the frequency and hazards of fires in this area. The occurrence of fire is closely related to factors such as terrain, climate and human activities. [0003] Existing technologies mainly use multiple linear regression models and correlation analysis to analyze the relationship between industrial park fire risk and impact factors; the inventors have found through research that multiple linear regression models and correlation analysis in the prior art are used to analyze industrial park fire risks and impacts The relationship between factors has at least the following defects: [0004] It only reflects the linear relationship between va...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06Q10/04G06Q10/06G06K9/62G06F111/10
CPCG06F30/27G06Q10/04G06Q10/0635G06F2111/10G06F18/214
Inventor 侯晓静毛文锋刘馨泽袁纪武王正曹永友
Owner CHINA PETROLEUM & CHEM CORP
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