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Evaluation method and system based on LOGISTIC regression model

An evaluation method and model technology, applied in complex mathematical operations, instruments, data processing applications, etc., can solve problems such as large amount of data, inaccurate model fitting results, and low evaluation accuracy of evaluation schemes

Pending Publication Date: 2020-08-25
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present invention provides a projection screen automatic correction method and system to solve the existing technical problems of large amount of data for evaluation based on the Logistic regression model, inaccurate model fitting results and low evaluation accuracy of the evaluation scheme

Method used

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  • Evaluation method and system based on LOGISTIC regression model
  • Evaluation method and system based on LOGISTIC regression model
  • Evaluation method and system based on LOGISTIC regression model

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Embodiment 1

[0052] An embodiment of the present invention is an evaluation method based on a Logistic regression model, figure 1 The method flowchart of the evaluation method based on the Logistic regression model provided by Embodiment 1 of the present invention; the method includes:

[0053]S101, dividing the area to be evaluated into grids of the same size;

[0054] Correspondingly, the dividing the area to be evaluated into grids of the same size includes: determining the size of the grids according to the size of the scale in the area to be evaluated.

[0055] In practical applications, the grid size is determined according to the scale size of the indicator data within the study area, and the formula used is:

[0056] G s =7.5+0.0006s-2.01×10 9 S 2 +2.91×10 15 S 3

[0057] In the formula: G s is the grid size, and S is the size of the basic data scale, thus determining the grid size.

[0058] S102. Obtain the number of first event points in the grid, and determine whether t...

Embodiment 2

[0084] An evaluation system based on the Logistic regression model in the embodiment of the present invention, such as image 3 Shown is the structural representation of the evaluation system based on the Logistic regression model provided by the embodiment of the present invention, and the system includes:

[0085] A division unit 301, which divides the area to be evaluated into grids of the same size;

[0086] Correspondingly, the dividing unit 301 includes: determining the size of the grid according to the size of the scale in the area to be evaluated.

[0087] In practical applications, the grid size is determined according to the scale size of the indicator data within the study area, and the formula used is:

[0088] G S =7.5+0.0006S-2.01×10 9 S 2 +2.91×10 15 S 3

[0089] In the formula: G s is the grid size, and S is the size of the basic data scale, thus determining the grid size.

[0090] The determination unit 302 is to obtain the number of first event point...

Embodiment 3

[0116] The present invention is based on the evaluation method and system based on the Logistic regression model proposed in the first and second embodiments above, and performs model verification and analysis in combination with data.

[0117] The present invention adopts 1108 historical disaster points in a certain city to carry out experiments, among which 80% (886 disaster points) are used for generating models, and 20% (222 disaster points) are used for model verification.

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Abstract

The invention provides an evaluation method and system based on a Logistic regression model, and belongs to the technical field of models and evaluation. The method comprises the steps of dividing a to-be-evaluated region into grids with the same size; obtaining the number of first event points in the grid, and determining whether the grid is a first grid and whether grids around the grid are first grids or not according to the number of the first event points in the grid; wherein the first event point corresponds to a first evaluation index; obtaining a first grid evaluation index according to a first evaluation index in the first grid; and according to the first grid evaluation index and a Logistic regression model, calculating the probability of occurrence of the first event in the evaluation area. The property of each disaster grid is determined by counting the number and positions of event points in the grid, and regression analysis is carried out according to the property, so that the precision of a simulated regression result is improved, the weight information of each evaluation index can be calculated more accurately, and higher evaluation precision is obtained.

Description

technical field [0001] The invention relates to the technical field of model evaluation, in particular to an evaluation method and system based on a Logistic regression model. Background technique [0002] At present, the commonly used evaluation methods for geological hazards are all based on the index weight, that is, use the corresponding mathematical model to obtain the sub-weight of each index, and then use the linear weighted summation method to evaluate the total value of the study area, and calculate the total value according to the relevant standards. The evaluation results are graded to obtain the zoning results of geological disaster susceptibility. [0003] Among them, the methods for determining the weight of evaluation indicators can be divided into two categories: subjective weight determination methods and objective weight determination methods. The subjective weight determination method is represented by the Analytical Hierarchy Process (AHP), which is main...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F17/18
CPCG06Q10/06393G06F17/18
Inventor 陈朝亮钱静彭树宏胡增运
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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