• Spectroscopy and Spectral Analysis
  • Vol. 44, Issue 3, 731 (2024)
TANG Jie1, LUO Yan-bo2, LI Xiang-yu2, CHEN Yun-can1, WANG Peng1, LU Tian3, JI Xiao-bo4, PANG Yong-qiang2、*, and ZHU Li-jun1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
  • show less
    DOI: 10.3964/j.issn.1000-0593(2024)03-0731-06 Cite this Article
    TANG Jie, LUO Yan-bo, LI Xiang-yu, CHEN Yun-can, WANG Peng, LU Tian, JI Xiao-bo, PANG Yong-qiang, ZHU Li-jun. Study on One-Dimensional Convolutional Neural Network Model Based on Near-Infrared Spectroscopy Data[J]. Spectroscopy and Spectral Analysis, 2024, 44(3): 731 Copy Citation Text show less

    Abstract

    Near-infrared spectroscopy technology has been widely applied for detection in various industries. However, traditional methods struggle to gather key information from the spectral data, leading to significant model prediction errors. This study explores the regression modeling of one-dimensional convolutional neural networks (1DCNN) on near-infrared data, focusing on the chemical composition of 452 plants from the Solanaceae family. Through parameter optimization, the study suggests that the optimal settings for the model include 64 channels in the intermediate convolutional layer, a maximum pooling layer of 1, 6 convolutional layers, and 5 channels in the final convolutional layer. These findings can serve as a reference for future model research. The root mean square error of the models test set ranges from 0.02 to 0.49, with an average relative error of 0.8%~1.7%, significantly lower than previous literature. Compared to traditional methods, 1DCNN can fully utilize all of the near-infrared spectral data while maintaining a simple model structure and strong predictive capabilities. This work provides new insights for data processing in near-infrared spectroscopy research and promotes the application and development of this technology.
    TANG Jie, LUO Yan-bo, LI Xiang-yu, CHEN Yun-can, WANG Peng, LU Tian, JI Xiao-bo, PANG Yong-qiang, ZHU Li-jun. Study on One-Dimensional Convolutional Neural Network Model Based on Near-Infrared Spectroscopy Data[J]. Spectroscopy and Spectral Analysis, 2024, 44(3): 731
    Download Citation