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A Big Data Processing Method Based on Stepwise Regression Analysis

A technology of big data processing and gradual regression, applied in the field of processing big data, it can solve problems such as the inoperability of algorithms, and achieve the effect of ensuring production safety, improving labor conditions, and improving equipment utilization ability.

Inactive Publication Date: 2019-06-14
CHINA UNIV OF MINING & TECH YINCHUAN COLLEGE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This creates a problem of how to select some independent variables that have a significant impact on the dependent variable from a large number of possible independent variables. There are many elements in the entire set of possible independent variables, and the algorithm using the "optimal" subset may work. unreasonable
Then the automatic search method that gradually generates the subset of X variables to be included in the regression model may be effective

Method used

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  • A Big Data Processing Method Based on Stepwise Regression Analysis
  • A Big Data Processing Method Based on Stepwise Regression Analysis
  • A Big Data Processing Method Based on Stepwise Regression Analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] Using the big data processing method based on stepwise regression analysis, first collect the mill data of a pulverized coal plant. The mill has 19 parameters in total. The number of each parameter is as follows in Table 1:

[0024] Numbering

parameter

Numbering

parameter

Numbering

parameter

1

Secondary fan frequency

2

Furnace temperature

3

Furnace negative pressure

4

Tail temperature

5

Furnace outlet temperature

6

Outlet temperature of air distribution chamber

7

Coal feeder frequency

8

actual traffic

9

Mill inlet temperature

10

Mill inlet pressure

11

Oxygen at the inlet of the mill

12

Oxygen at the inlet of the mill

13

Mill outlet pressure

14

Cyclone temperature

15

Bag inlet temperature

16

Bag outlet temperature

17

ID fan frequency

18

1# powder storage tower temperature

19

2# powder storage t...

Embodiment 2

[0056] Using the big data processing method based on stepwise regression analysis, the operation data of a pulverized coal boiler in a heating company is collected. The pulverized coal boiler has a total of 65 parameters. The number of each parameter is as follows in Table 2:

[0057]

[0058]

[0059] Taking the above-mentioned parameters 1-65 as dependent variables and the remaining parameters as independent variables, the following equation can be obtained:

[0060]

[0061] Among them: the subscripts of y and x indicate the number of the parameter, and b is the intercept.

[0062] Import the above equations and corresponding data into Matlab software one by one, perform stepwise regression analysis and calculation, and find the coefficient before the independent variable. If an independent variable has no influence on the dependent variable, the coefficient before the independent variable is zero, and finally the following results are obtained:

[0063]

[0064...

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Abstract

The present invention relates to a stepwise regression analysis-based big data processing method. The method includes the following steps of firstly, collecting data of factory operation parameters, and numbering the collected operation parameters; then, using some of the collected operation parameters as dependent variables, using other operation parameters as independent variables, and writing equations, wherein the parameters are in a linear relationship; then, importing the equations and corresponding data into Matlab software one by one, performing stepwise regression analysis operation, and calculating a coefficient and an intercept of each equation before the independent variable; and finally, performing result analysis so as to obtain an optimal value of a corresponding operation parameter. According to the method, a lot of data is collected, stepwise regression analysis and big data processing are performed, the Matlab software is used, and the impact of all operation parameters of a factory DCS is determined quantitatively so as to quantitatively determine and change the impact of a certain parameter on other parameters to determine the optimal value of a factory DCS operation parameter.

Description

Technical field: [0001] The invention relates to a method for processing big data in industrial production, in particular to a method for processing big data based on stepwise regression analysis. Background technique: [0002] Regression analysis is a mathematical method to deal with the correlation among multiple variables. This correlation is different from the functional relationship. The latter reflects the strict dependence between variables, while the former shows a certain degree of volatility or randomness. For each value of the independent variable, the dependent variable can have multiple values ​​and corresponding to it. When the independent variable is a non-random variable and the dependent variable is a random variable, analyzing their relationship is called regression analysis; when both are random variables, it is called correlation analysis. Regression analysis and correlation analysis can be used to study correlation in statistics. Although there is som...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/18
CPCG06F17/18
Inventor 魏亚玲李东张学梅苗泽凯程实马青华
Owner CHINA UNIV OF MINING & TECH YINCHUAN COLLEGE
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