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Forecasting method of baking sheet smoke

A prediction method and flue gas technology, applied in prediction, data processing application, calculation, etc., can solve the problems of time-consuming and laborious detection process and high detection cost, and achieve the effect of ensuring robustness and good estimation effect.

Inactive Publication Date: 2013-04-03
HONGTA TOBACCO GRP
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Problems solved by technology

The smoke data obtained in this way needs to be rolled into cigarettes for chemical detection of smoke after burning. The detection process is time-consuming and labor-intensive and the detection cost is extremely high.

Method used

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  • Forecasting method of baking sheet smoke
  • Forecasting method of baking sheet smoke
  • Forecasting method of baking sheet smoke

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Embodiment Construction

[0029] The present invention is based on the robust regression modeling method for predicting the flue gas of grilled slices or the system client runs on the Windows platform, and the server adopts the SQL SERVER database system.

[0030] The smoke prediction system based on robust regression modeling of the present invention mainly includes two major contents:

[0031] Content 1: Modeling based on the known smoke data of the grill;

[0032] Content 2: Use a robust regression model to predict the smoke value of unknown roasted slices;

[0033] First, the present invention constructs a modeling system based on C / S mode, which mainly includes a database server and a model client. The client provides a user interface interaction window to accept user input information, provide an interactive interface for the modeling process, and display model prediction results. It is characterized by the following modules, and its system structure diagram is shown in the appendix figure 1 : ...

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Abstract

The invention relates to a forecasting method of baking sheet smoke, in particular to the baking sheet smoke forecasting method based on robust regression modeling. A model from physicochemical index object to a smoke index object is built through the existing baking sheet physicochemical data and smoke data, and a baking sheet smoke value of unknown baking sheet smoke data can be directly forecasted by using the physicochemical ingredient data. By means of a robust regression model, malpractices caused by singular value samples in the physicochemical data and the smoke data can be effectively avoided, robustness of the model can be guaranteed to great extent, the system can effectively forecast the smoke value of the baking sheet, and whole quality situations of the baking sheet can be well estimated.

Description

technical field [0001] The invention relates to a method for predicting flue gas of grilled slices, in particular to a method for predicting flue gas of grilled slices based on robust regression modeling. Background technique [0002] The smoke prediction of the baked sheet plays a vital role in the quality and sensory of cigarette products. The traditional way to obtain the smoke data of roasting slices is to detect the chemical composition indicators in the flue gas after burning the roasting slices. For the smoke data obtained in this way, it is necessary to chemically detect the smoke after the roasted sheet is rolled into a cigarette, and the detection process is time-consuming and labor-intensive, and the detection cost is extremely high. Therefore, it is imperative to propose a method to directly obtain flue gas data from the physical and chemical data of baked slices by building a model. Contents of the invention [0003] The invention proposes a prediction syste...

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Application Information

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IPC IPC(8): G06Q10/04
Inventor 白晓莉董伟牟定荣龚荣岗彭国岗
Owner HONGTA TOBACCO GRP
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