Prediction model of cigarette material and mainstream smoke composition based on genetic algorithm optimized neural network

A neural network model and neural network technology, applied in the field of prediction models of cigarette materials and mainstream smoke components

Inactive Publication Date: 2018-12-18
HUBEI CHINA TOBACCO IND
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Problems solved by technology

At present, neural network-related technologies have begun to be applied in the model of the relationship between cigarette sensory evaluation and mainstream smok

Method used

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  • Prediction model of cigarette material and mainstream smoke composition based on genetic algorithm optimized neural network
  • Prediction model of cigarette material and mainstream smoke composition based on genetic algorithm optimized neural network
  • Prediction model of cigarette material and mainstream smoke composition based on genetic algorithm optimized neural network

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Embodiment Construction

[0035] The present invention will be further explained below in conjunction with the drawings:

[0036] In this example, the entire experimental data set is divided into two parts, one is used as the training set of the BP neural network, and the other is used as the test set of the BP neural network. The data in the training set is taken as 2 / 3-4 / 5 of the total data volume . Definition D is an n×m data set, each row represents a data record, and each column represents an attribute. Let sets A and B denote the training set and the test set obtained by dividing the data set, respectively. First obtain the best neural network weights and thresholds based on the training set A based on genetic algorithm, and then use the best neural network weights and thresholds as the initial parameters for training the BP neural network model to train the neural network. When the output of the network matches expectations If the difference between the output results reaches a certain standard o...

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Abstract

A prediction model of cigarette material and mainstream smoke composition based on genetic algorithm optimized neural network comprises the following steps: sample pretreatment; obtaining the optimalweights and threshold parameters of neural network based on genetic algorithm; constructing and training the neural network based on the optimal weights and thresholds obtained by genetic algorithm. The trained neural network model is verified and the evaluation model is applied to the actual effect. Compared with the neural network without optimization algorithm, the neural network model based ongenetic algorithm firstly uses genetic algorithm to select the weights and thresholds to minimize the model error as the initial parameters of the training neural network, which can avoid the model falling into the local optimal solution, but can not get the global optimal solution.

Description

Technical field [0001] The invention relates to a prediction model, which belongs to the field of industrial design and production. It uses genetic algorithms to optimize neural networks to establish the mapping relationship between cigarette materials and mainstream smoke components, and reasonably adjusts the cigarette material formula for the cigarette manufacturing industry to produce cigarettes that meet specifications. Provides a model, specifically a neural network-based prediction model for cigarette materials and mainstream smoke components. Background technique [0002] In the tobacco manufacturing industry, the composition and content of harmful gases released by tobacco has always been a concern of tobacco manufacturing companies and consumers. In order to optimize product design, speed up production efficiency, and produce qualified and low-hazard products, the tobacco manufacturing industry needs to use statistical knowledge to perform canonical correlation analysis...

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Application Information

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IPC IPC(8): G06N3/08G06N3/12G06Q10/04
CPCG06N3/084G06N3/126G06Q10/04
Inventor 潘曦宋旭艳魏敏李冉郭国宁
Owner HUBEI CHINA TOBACCO IND
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