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Application Research of Weighted Fuzzy C Means Clustering about Soil Fertility Evaluation in Nong’an County

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Recent Advances in Computer Science and Information Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 124))

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Abstract

Changes in Cultivated Land Fertility has important influence on food production, productivity. In this paper, by using acquired land evaluation data of Nong’an County Jilin Province, using entropy method to calculate the weight of all evaluation data, and to improve the weight to the original fuzzy C means clustering algorithm, C means clustering algorithm was gained based on fuzzy entropy weight finally. We applied this algorithm to evaluate soil fertility Nong’an County Jilin Province to get the results of its evaluation, the average accuracy rate of 94.02%, indicating the algorithm can be applied to the soil fertility evaluation.

Funds support: National 863 subjects (2006AA10A309); Jilin Agricultural University Scientific Research Foundation.

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References

  1. Yue, Y., Li, T., Zhao, G., et al.: GIS supported quantitative evaluation of cultivated land fertility. Transactions of the CSAE 20(1), 307–310 (2004) (in Chinese)

    Google Scholar 

  2. Ma, W., Feng, Z.: Research on Relation between Integrated Grain Production Capacity and Cultivated Land Loss. Research of Agricultural Modernization 26(5), 353–357 (2005) (in Chinese)

    MATH  Google Scholar 

  3. Huang, J., Li, H.-M., Zhang, H.-L., et al.: Evaluation of Integrated Soil Fertilities of Cultivated Land at County Level in Jilin Province and a Evaluation Index System Based on GIS—A case study in Jiutai City. Chinese Journal of Soil Science 38(3), 422–426 (2007) (in Chinese)

    MathSciNet  Google Scholar 

  4. Ruspin, I.E.H.: A new approach to clustering. Information and Control 19(15), 22–32 (1969)

    Article  Google Scholar 

  5. Ruspin, I.E.H.: New experimental results in fuzzy clustering. Information Science 18(2), 273–287 (1973)

    Article  Google Scholar 

  6. Ruspin, I.E.H.: Numerical methods for fuzzy clustering. Information Science 15(2), 319–350 (1970)

    Article  Google Scholar 

  7. Tamra, S.: Pattern classification based on fuzzy relations. IEEE Trans. on Systems, Man, and Cybernetics 1(1), 217–242 (1971)

    Google Scholar 

  8. Zadeh, L.A.: Similarity relations and fuzzy orderings. Information Science 3(2), 177–200 (1971)

    Article  MATH  MathSciNet  Google Scholar 

  9. Backer, E., Jain, A.K.: A clustering performance measure based on fuzzy set decomposition. IEEE Trans. on Pattern Analysis and Machine Intelligence 3(1), 66–77 (1981)

    Article  MATH  Google Scholar 

  10. Le, Z.: Fuzzy relation compositions and pattern recognition. Information Science 89(1 /2), 107–130 (1996)

    Article  Google Scholar 

  11. Zahn, C.T.: Graph theoretical methods for detecting and describing gestalt clusters. IEEE Trans. on Computers 20(1), 68–86 (1971)

    Article  MATH  Google Scholar 

  12. Bin, D.: A Clustering Dynamic State Method of Maximal Tree of Fuzzy Graph Theory. Journal of Numerical Methods and Computer Applications 13(2), 157–159 (1992) (in Chinese)

    Google Scholar 

  13. Wu, Z., Leathy, R.: An optimal graph theoretic approach to data clustering theory and its application to image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence 15(11), 1101–1113 (1993)

    Article  Google Scholar 

  14. Bezdek, J.C., Fordon, W.A.: The application of fuzzy set theory to the medical diagnosis. In: Advances of Fuzzy Sets and Theories, pp. 445–461. North-Hollad, Amsterdam (1979)

    Google Scholar 

  15. Esogbue, A.O.: Optimal clustering of fuzzy data via fuzzy dynamic programming. Fuzzy Sets and Systems 18(3), 283–298 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  16. Mantaras, R.L.D., Valverde, L.: New results in fuzzy clustering based on the concept of indistinguishable relation. IEEE Trans. on Pattern Analysis and Machine Intelligence 10(5), 754–757 (1988)

    Article  MATH  Google Scholar 

  17. Hu, C., Qin, X.: Spatial Classification and Prediction Based on Fuzzy c-means. Journal of Computer Research and Development 45(7), 1183–1188 (2008) (in Chinese)

    Google Scholar 

  18. Zhu, Q., Guo, P.: An Entropy-based Evaluation Model for Multiple Objective Decision Making in Port Resources. Journal of Shandong Agricultural University 36(2), 258–265 (2005) (in Chinese)

    MathSciNet  Google Scholar 

  19. Huang, S., Huang, W.: Based on entropy and the VA GU E set of multi-objective decision making. Chinese Journal of Management (2), 120–123 (2005) (in Chinese)

    Google Scholar 

  20. Li, P., Wei, C., Qiu, D.: Potentiality Evaluation of Regional Cultivated Land Consolidation and Rehabilitation Based on Entropy Weight method: A Case Study of Chongqing Municipality. Chinese Agricultural Science Bulletin 23(6), 536–541 (2007) (in Chinese)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Jilin Agricultural University, Chang Chun, China

    Guowei Wang, Li Yan & Yuxia Yao

Authors
  1. Guowei Wang
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  2. Li Yan
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  3. Yuxia Yao
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Editor information

Editors and Affiliations

  1. College of Communication Engineering, Jilin University, Room 313, Building No.1, Changchun, Nanhu Avenue 5372, 130012, Jilin, China, People’s Republic

    Zhihong Qian

  2. Department of Electrical Engineering, The University of Mississippi, Anderson Hall 314, 38677, Mississippi, Mississippi, USA

    Lei Cao

  3. Department of Electrical and Computer Eng., Naval Postgraduate School, Rm. 452 Spanagel Bldg. 232, Dyer Road 833, 93943-5121, Monterey, California, USA

    Weilian Su

  4. Faculty of Computing, London Metropolitan University, Holloway Road 166-220, N7 8DB, London, United Kingdom

    Tingkai Wang

  5. College of Software, Changchun University of Science and Tech., Changchun, 130022, Jilin, China, People’s Republic

    Huamin Yang

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, G., Yan, L., Yao, Y. (2012). Application Research of Weighted Fuzzy C Means Clustering about Soil Fertility Evaluation in Nong’an County. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25781-0_30

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  • DOI: https://doi.org/10.1007/978-3-642-25781-0_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25780-3

  • Online ISBN: 978-3-642-25781-0

  • eBook Packages: EngineeringEngineering (R0)

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