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Mildew Prediction Model of Warehousing Tobacco Based on Particle Swarm Optimization and BP Neural Network

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Book cover Intelligent Computing Methodologies (ICIC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11645))

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Abstract

In order to reduce the economic loss caused by mildew of warehousing tobacco, in this paper, particle swarm optimization algorithm is introduced into BP neural network mode. Particle swarm optimization is used to dynamically adjust the initial weights and thresholds of BP neural network. PSO-BP neural network prediction model is established to predict mildew of warehousing tobacco. Simulation experiment results show that the PSO-BP neural network model proposed in this paper is compared with the traditional BP neural network model. The prediction accuracy of warehousing tobacco mildew is higher. The effectiveness of the algorithm is verified.

Key Project of Yunnan Applied Basic Research Program (grant No. 2018FA033)

National Science Foundation of China (grant No. 61865015)

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References

  1. Zhang, C., Wang, H.: Analysis of factors affecting the mildew of storage slices. Chin. Tob. Sci. 32(3), 80–83 (2011)

    MathSciNet  Google Scholar 

  2. Zhang, L., Ma, J.: Prediction of storage tobacco mildew based on BP neural network. J. East China Jiaotong Univ. 30(3), 71–75 (2013)

    Google Scholar 

  3. Li, J.: Research on improving convergence speed of BP wavelet neural network. Pattern Recognit. Artif. Intell. 15(1), 28–35 (2002)

    Google Scholar 

  4. Huang, L.: A review of particle swarm optimization algorithm. Mech. Eng. Autom. (5), 197–199

    Google Scholar 

  5. Yan, P., Zhang, C.: Artificial Neural Network and Simulated Evolutionary Computation. Tsinghua University Press, Beijing (2006)

    Google Scholar 

  6. Chen, G.: Analysis and optimization of factors influencing prediction accuracy of neural network model. Pattern Recognit. Artif. Intell. 18(5), 528–534 (2005)

    Google Scholar 

  7. Jiao, B., Ye, M.: Method of BP neural network nodes determination in hidden layer. J. Shanghai Dianji Univ. 16(3), 113–116 (2013)

    Google Scholar 

  8. Haykin, S.: Neural Network A Comprehensive Foundation, 2nd edn, pp. 109–123. China Machine Press, Beijing (2004)

    Google Scholar 

  9. Yang, W., Zhang, X.: Overview of particle swarm optimization algorithm. Gansu Sci. Technol. 28(5), 88–92 (2012)

    Google Scholar 

  10. Zhang, Q., Meng, X.: Particle swarm optimization algorithm based on random dimension partitioning and learning. J. Zhejiang Univ. (Eng. Ed.) 52(02), 367–378 (2018)

    Google Scholar 

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Acknowledgment

This work is funded by grants from the National Science Foundation of China (grant No. 61865015) and by Key Project of Applied Basic Research Program of Yunnan Province (grant No. 2018FA033).

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Authors and Affiliations

  1. Information School, Yunnan Normal University, Kunming, 650500, Yunnan, China

    Zhixia Ye, Lijun Yun, Jingchao Zhang & Yibo Wang

  2. Yunnan Key Laboratory of Optoelectronic Information Technology, Kunming, 650500, Yunnan, China

    Zhixia Ye & Lijun Yun

  3. YCIH NO.2 Construction Co. Ltd., Kunming, 650203, Yunnan, China

    Huijun Li

Authors
  1. Zhixia Ye
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  2. Lijun Yun
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  3. Huijun Li
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  4. Jingchao Zhang
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  5. Yibo Wang
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Corresponding author

Correspondence to Lijun Yun .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Nanchang Institute of Technology, Nanchang, China

    Zhi-Kai Huang

  3. Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Ye, Z., Yun, L., Li, H., Zhang, J., Wang, Y. (2019). Mildew Prediction Model of Warehousing Tobacco Based on Particle Swarm Optimization and BP Neural Network. In: Huang, DS., Huang, ZK., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Computer Science(), vol 11645. Springer, Cham. https://doi.org/10.1007/978-3-030-26766-7_21

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  • DOI: https://doi.org/10.1007/978-3-030-26766-7_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26765-0

  • Online ISBN: 978-3-030-26766-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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