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Prediction method of coal calorific value on the basis of grey correlation analysis and multiple linear regression model

A technology of multiple linear regression and gray relational analysis, which is applied in forecasting, instrumentation, data processing applications, etc., and can solve problems such as time-consuming, manpower, and material resources

Inactive Publication Date: 2016-07-06
NANJING DELTO TECH
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Problems solved by technology

In actual industrial production, relying on experimental methods to determine the calorific value of coal needs to consume a certain amount of manpower and material resources, and it takes a long time

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  • Prediction method of coal calorific value on the basis of grey correlation analysis and multiple linear regression model
  • Prediction method of coal calorific value on the basis of grey correlation analysis and multiple linear regression model
  • Prediction method of coal calorific value on the basis of grey correlation analysis and multiple linear regression model

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Embodiment Construction

[0033] The present invention can be better understood from the following examples. However, those skilled in the art can easily understand that the content described in the embodiments is only for illustrating the present invention, and should not and will not limit the present invention described in the claims.

[0034] combined with figure 1 , taking a set of coal quality data of the 18th mine reported by a coal mine testing center in 2014 as an example, the five indicators of coal moisture, ash content, volatile matter, the maximum thickness of the colloidal layer, and the carbon-oxygen atomic ratio were selected for comparison with the calorific value of coal. Correlation analysis requires that the calorific value of coal can be predicted, and the relative error of prediction should not exceed ±8%.

[0035] Collect coal moisture, ash, volatile matter, maximum thickness of colloidal layer, carbon-oxygen atomic ratio, calorific value and other parameter data, and establish ...

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Abstract

The invention discloses a prediction method for establishing a multiple linear regression model on the basis of a grey correlation analysis method so as to predict a coal calorific value. The method carries out correlation analysis on the coal calorific value and five indexes including moisture, ash content, volatile components, gelatinous layer maximum thickness and an oxygen and carbon atomic ratio to find a main impact factor associated with the coal calorific value and establish the multiple linear regression model so as to predict the coal calorific value. The method adopts a correlation analysis method in a grey system theory to analyze five factors which affect the coal calorific value, a main factor which affects the coal calorific value is picked up from the five factors, and the multiple linear regression model between the coal calorific value and the main impact factor is established. The prediction method of the coal calorific value is simple and feasible and is high in prediction precision, and a relative prediction error does not exceed + / -8%.

Description

technical field [0001] The invention relates to a method for predicting industrial production data, in particular to a method for predicting the calorific value of coal by using industrial analysis data of coal. Background technique [0002] The calorific value of coal is an important analysis content in coal research and analysis. In the coal classification standards at home and abroad, the calorific value of coal can be used as one of the important standards for coal classification. There are two main ways to obtain the calorific value of coal, one is to measure through experiments, and the other is to calculate through prediction models. In actual industrial production, relying on experimental methods to determine the calorific value of coal needs to consume a certain amount of manpower and material resources, and it takes a long time. Therefore, it is necessary to establish a prediction model that conforms to the characteristics of coal and to develop a method for effec...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/02
CPCG06Q10/04G06Q50/02
Inventor 童国道唐声阳朱丽平沈启鹏
Owner NANJING DELTO TECH
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