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Homeomorphism Between Fuzzy Number Space and the Space of Bounded Functions with Same Monotonicity on \([-1,1]\)

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Data Science (ICDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9208))

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Abstract

In this paper, based on the fuzzy structured element, we prove that there is a bijection function between the fuzzy number space \(\varepsilon ^1\) and the space \(B[-1, 1]\), which defined as a set of standard monotonic bounded functions with monotonicity on interval \([-1, 1]\). Furthermore, a new approach based upon the monotonic bounded functions has been proposed to create fuzzy numbers and represent them by suing fuzzy structured element. In order to make two different metrics based space in \(B[-1, 1]\), Hausdorff metric and \(L_p\) metric, which both are classical functional metrics, is adopted and their topological properties is discussed. In addition, by the means of introducing fuzzy functional to space \(B[-1, 1]\), we present two new fuzzy number’s metrics. Finally, according to the proof of homeomorphism between fuzzy number space \(\varepsilon ^1\) and the space \(B[-1, 1]\), it’s argued that not only it gives a new way to study the fuzzy analysis theory, but also make the study of fuzzy number space easier.

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References

  1. Cong-Xin, W., Ming, M.: Embedding problem of fuzzy number space: part I. Fuzzy Sets Syst. 44(1), 33–38 (1991)

    Article  Google Scholar 

  2. Congxin, W., Ming, M.: Embedding problem of fuzzy number space: part II. Fuzzy Sets Syst. 45(2), 189–202 (1992)

    Article  MATH  Google Scholar 

  3. Diamond, P., Kloeden, P.: Characterization of compact subsets of fuzzy sets. Fuzzy Sets Syst. 29(3), 341–348 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  4. Diamond, P., Kloeden, P.: Metric spaces of fuzzy sets. Fuzzy Sets Syst. 35(2), 241–249 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  5. Diamond, P., Kloeden, P.E., Kloeden, P.E., Mathematician, A., Kloeden, P.E.: Metric Spaces of Fuzzy Sets: Theory and Applications. World Scientific, Singapore (1994)

    Book  MATH  Google Scholar 

  6. Gergó, L.: Generalisation of the Goetschel-Voxman embedding. Fuzzy Sets Syst. 47(1), 105–108 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  7. Goetschel, R., Voxman, W.: Topological properties of fuzzy numbers. Fuzzy Sets Syst. 10(1), 87–99 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  8. Guo, S., Su, Z., Wang, L.: Method of structured element in fuzzy analysis and calculation. Fuzzy Syst. Math. 3, 011 (2004)

    Google Scholar 

  9. Guo, S.: Method of structuring element in fuzzy analysis. J. Liaoning Tech. Univ. 21(5), 670–673 (2002)

    Google Scholar 

  10. Li, A., Shi, Y., He, J., Zhang, Y.: A fuzzy linear programming-based classification method. Int. J. Inf. Tech. Decis. Making 10(06), 1161–1174 (2011)

    Article  MATH  Google Scholar 

  11. Lin, K., Pai, P., Lu, Y., Chang, P.: Revenue forecasting using a least-squares support vector regression model in a fuzzy environment. Inf. Sci. 220, 196–209 (2013)

    Article  Google Scholar 

  12. Puri, M.L., Ralescu, D.A.: Differentials of fuzzy functions. J. Math. Anal. Appl. 91(2), 552–558 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  13. Reuter, U.: A fuzzy approach for modelling non-stochastic heterogeneous data in engineering based on cluster analysis. Integr. Comput. Aided Eng. 18(3), 281–289 (2011)

    Google Scholar 

  14. Wang, H., Guo, S., Yue, L.: An approach to fuzzy multiple linear regression model based on the structural element theory. Syst. Eng. Theor. Pract. 34(10), 2628 (2014)

    Google Scholar 

  15. Yang, M.S., Ko, C.H.: On a class of fuzzy c-numbers clustering procedures for fuzzy data. Fuzzy Sets Syst. 84(1), 49–60 (1996)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This work has been partially supported by grants from National Natural Science Foundation of China (Grant NO.71331005, NO.71110107026.)

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Correspondence to Yong Shi .

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Wang, H., Guo, S., Shi, Y. (2015). Homeomorphism Between Fuzzy Number Space and the Space of Bounded Functions with Same Monotonicity on \([-1,1]\) . In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-24474-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24473-0

  • Online ISBN: 978-3-319-24474-7

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