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Research on Apple Yield Prediction Model

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1074))

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Abstract

This paper has used a fuzzy comprehensive prediction method and taken tree vigor data from 29 orchards as samples. By using 23 of the total samples, the apple yield prediction model base on tree vigor is established. The test precision of the model is 96.36%. With other six orchards to be predicted, this paper calculated fuzzy division and eigenvalues of grade variables and obtained apple yield prediction accuracy which is 91.08%. This model has practical applied value in apple yield prediction.

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References

  1. Sun, Z., Sun, Z., Yang, Z., Wang, Y.: Advances on research and application of mathematical simulation in fruit tree ecophysiology. J. Fruit Sci. 4, 361–366 (2005)

    Google Scholar 

  2. Cong, Y., Jun, W.: A comparative study on forecast models of apple output in China. J. Fruit Sci. 5, 682–684 (2007)

    Google Scholar 

  3. Xuelong, Q., Guiping, W., Hua, M.: Research on combination forecasting model of apple output based on genetic algorithm. J. Fruit Sci. 1, 165–170 (2011)

    Google Scholar 

  4. Liu, L., Wang, J., Qu, Z., Gao, F., Chai, Q., Yi, L.: Research on non-linear regression model of meteorological factors for apple yield in Shaanxi Province. Chin. Agric. Sci. Bull. 25, 248–251 (2012)

    Google Scholar 

  5. Li, X., Zong, X., Li, J., Shang, Y., Li, F.: Fuzzy comprehensive prediction model and its application. J. Shandong Agric. Univ. (Nat. Sci.) 2, 169–173 (2003)

    Google Scholar 

  6. Zhu, X., Jiang, Y., Zhao, G., Wang, L., Li, X.: Hyperspectral estimation of kalium content in apple florescence canopy based on fuzzy recognition. Spectroscopy Spectral Anal. 4, 1023–1027 (2013)

    Google Scholar 

  7. Li, X., Xie, M., Xu, D., Duan, J.: On theoretic model of fuzzy classification and fuzzy recognition. Fuzzy Syst. Math. 2, 58–64 (2002)

    Google Scholar 

  8. Li, X., Wang, J., Wang, F., Du, J.: Spectral retrieved deduction of soil properties index based on fuzzy recognition theory. J. Liaoning Tech. Univ. (Nat. Sci.) 2, 324–327 (2010)

    Google Scholar 

  9. Robinson, T.L., Lakso, A.N.: Modifying apple tree canopies for improved production efficiency. Hortsince 8, 1005–1012 (1991)

    Google Scholar 

  10. Lokso, A.N., Grappadelli, L.C.: Implication of pruning and training practices to Carbon partitioning and fruit development in apple. Acta Hort 322, 231–239 (1992)

    Google Scholar 

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Correspondence to Shuhan Cheng .

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Wang, Z., Li, X., Wang, Y., Cheng, S. (2020). Research on Apple Yield Prediction Model. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_98

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