Application of radial basis function neural network in optimization of process parameters of cigarette silk making

Leiping Cheng; Xiaoyan Wu; Peng Xie; Shisheng Jiang

doi:10.1117/12.3011375

8 November 2023 Application of radial basis function neural network in optimization of process parameters of cigarette silk making

Leiping Cheng, Xiaoyan Wu, Peng Xie, Shisheng Jiang

Author Affiliations +

Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 1292325 (2023) https://doi.org/10.1117/12.3011375
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China

Abstract

In view of the instability of the existing cigarette quality control level, there are still large fluctuations in the physical characteristics of tobacco, physical characteristics of tobacco and cigarette smoke quality control indicators. The radial basis function neural network (RBFNN) has the advantages of simple structure, fast convergence and overcoming the local minimum problem. The prediction model of RBFNN cigarette silk process quality control index was established, the parameters of cigarette silk process were optimized, and the optimized results were compared with the traditional orthogonal test results. The results show that the prediction model of RBFNN technology quality control index for cigarette silk production has high accuracy, while the traditional orthogonal test method has differences in parameter setting. Therefore, RBFNN is more accurate in predicting the optimal technological parameters of cigarette silk making and improves the production efficiency of cigarette silk making.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Leiping Cheng, Xiaoyan Wu, Peng Xie, and Shisheng Jiang "Application of radial basis function neural network in optimization of process parameters of cigarette silk making", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 1292325 (8 November 2023); https://doi.org/10.1117/12.3011375

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