Prediction method of the moisture content of the cigarette cut out based on BP neural network optimized by GA algorithm

Zhiwen Fu; Ying Liang

doi:10.1117/12.2675265

25 May 2023 Prediction method of the moisture content of the cigarette cut out based on BP neural network optimized by GA algorithm

Zhiwen Fu, Ying Liang

Author Affiliations +

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126361Q (2023) https://doi.org/10.1117/12.2675265
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

In the process of cigarette making, loose moisture regain, as one of the most important processes, plays an indispensable role in production efficiency and product quality. In order to solve the problem of low control accuracy of export moisture content, this paper analyzes the data of influencing factors collected by the existing automation system of cigarette factory, mainly focuses on BP neural network, and uses GA genetic algorithm to optimize and adjust the initial weight of BP neural network, A high precision prediction model with global search capability is established to accurately predict the water content at the outlet of the loose water regain process. The experimental results show that the prediction model has higher prediction accuracy than the traditional BP neural network, and effectively improves the accuracy of the prediction system.

Citation Download Citation

Zhiwen Fu and Ying Liang "Prediction method of the moisture content of the cigarette cut out based on BP neural network optimized by GA algorithm", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126361Q (25 May 2023); https://doi.org/10.1117/12.2675265

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