Skip to main content

E-Commerce Profit Evaluation of Agricultural Products Based on Grey Prediction Algorithm

  • Conference paper
  • First Online:
  • 980 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1233))

Abstract

In the present society, we have gradually begun to use computer technology for the study of the development of agriculture and research. We also began to use computers for research on the computational studies of e-commerce profitability evaluation for agricultural products. Through computer computing research, it will be more convenient and fast to analyze and research the profitability of agricultural products in e-commerce. This paper uses the grey forecasting algorithm to evaluate the profitability of e-commerce in agricultural products. It is one of the directions for the above problems, and it has gradually achieved good results. Through our testing of the algorithm, we find that the algorithm is highly reliable in the calculation and use of this paper.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Zeng, B., Liu, S.: A self-adaptive intelligence gray prediction model with the optimal fractional order accumulating operator and its application. Math. Methods Appl. Sci. 40, 7843–7857 (2017)

    Article  MathSciNet  Google Scholar 

  2. Liu, X., Fine, J.P., Chen, Z., et al.: Prediction of the 20-year incidence of diabetes in older Chinese: application of the competing risk method in a longitudinal study. Medicine 95(40), 5057 (2016)

    Article  Google Scholar 

  3. Vani, R., Sangeetha, M.: A new hybrid search algorithm with novel cross-diagonal-hexagon search video coding algorithm for block motion estimation. Wirel. Pers. Commun. 88(2), 211–222 (2016)

    Article  Google Scholar 

  4. Lim, H., Gray, P., Xie, L., et al.: Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem. Sci. Rep. 6, 38860 (2016)

    Google Scholar 

  5. Li, W., Lu, C., Liu, S.: The research on electric load forecasting based on nonlinear gray bernoulli model optimized by cosine operator and particle swarm optimization. J. Intell. Fuzzy Syst. 30(6), 3665–3673 (2016)

    Article  Google Scholar 

  6. Barion, G., Mosca, G., Vamerali, T.: Estimation of cotyledon isoflavone abundance by a gray luminance-based model in variously hilum-colored soybean varieties. J. Sci. Food Agric. 96(12), 4126–4134 (2016)

    Article  Google Scholar 

  7. Liu, H.F., Ren, C., Zheng, Z.T., et al.: Study of a gray genetic BP neural network model in fault monitoring and a diagnosis system for dam safety. Int. J. Geo-Inf. 7(1), 4 (2017)

    Article  Google Scholar 

  8. Sun, X., Sun, W., Wang, J., et al.: Using a Grey–Markov model optimized by Cuckoo search algorithm to forecast the annual foreign tourist arrivals to China. Tour. Manag. 52, 369–379 (2016)

    Article  Google Scholar 

  9. Wang, H.T., Wang, T.C.: Application of the grey Lotka-Volterra model to forecast the diffusion and competition analysis of the TV and smartphone industries. Technol. Forecast. Soc. Chang. 106, 37–44 (2016)

    Article  Google Scholar 

  10. Trinh, H.X.P., Tran, T.T.: An analyzing case: numbers of Taiwanese students and their expenditures by using grey system theory to forecast. Int. J. Adv. Appl. Sci. 4(9), 35–45 (2017)

    Article  Google Scholar 

Download references

Acknowledgements

Jilin provincial department of education “13th five-year” social science project “research on cross-border e-commerce development strategy of jilin province agricultural products export from the perspective of ‘One Belt And One Road’ (JJKH20190777SK)”;Research project of jilin normal university of engineering and technology “research on restricting factors and coping strategies of rural e-commerce development in jilin province (XYB201831)”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shuangying Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, S. (2021). E-Commerce Profit Evaluation of Agricultural Products Based on Grey Prediction Algorithm. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51431-0_5

Download citation

Publish with us

Policies and ethics