Cigarette sensory quality evaluation method based on multi-classifier integration

Abstract

The invention provides a cigarette sensory quality evaluation method based on multi-classifier integration. The method comprises the following steps: acquiring finished cigarette sensory quality to-be-evaluated data, namely, cigarette chemical component indexes; performing normalization processing on the acquired finished cigarette sensory quality to-be-evaluated data based on finished cigarette sensory evaluation history data; performing cigarette sensory quality evaluation by using a cigarette sensory quality evaluation model based on multi-classifier integration to obtain a cigarette sensory quality evaluation result. The cigarette sensory quality evaluation method based on multi-classifier integration is applied to the product design and evaluation processes of finished cigarettes in cigarette enterprises. When cigarette experts perform sensory quality evaluation, a plurality of practically-measured chemical component indexes are given specific to a certain cigarette finished product, so that the sensory quality evaluation result of the product can be obtained at high accuracy, and decisions are made instead of or in a way of assisting the experts in product production and design processes.

Description

technical field [0001] The invention relates to the fields of information technology and automation technology, in particular to a method for evaluating the sensory quality of cigarettes based on multi-classifier integration. Background technique [0002] In the process of cigarette production, it is difficult to establish an effective mathematical model for the complex relationship between the physical and chemical indicators of tobacco and the sensory quality of cigarettes. Therefore, in the process of new product development and product maintenance of tobacco and its products, tobacco experts mainly The sensory quality indicators of cigarette products were evaluated by artificial sensory evaluation. Obviously, this kind of production method that completely relies on manual repeated evaluation will greatly affect the efficiency of evaluation results, and cannot meet the requirements of enterprises for rapid production. [0003] In order to solve the problems of strong sub...

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Problems solved by technology

[0004] However, for the sensory evaluation history data that exists in the form of continuous data, most of the existing studies use the fitting prediction method to evaluate the sensory quality of cigarettes. For the evaluation process of smoking experts, each expert takes 0.5 as The evaluation index is scored in this section, and the continuous data used in the experiment is actually the average value of the scores of multiple experts, that is, the evaluation results of each expert that meet the requirements of the enterprise are actually discrete

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