Abstract
The purpose of this paper is to present a new approach of city leisure index (CLI). We are comprehensive estimates of the recreational functions of cities and the development of a quantitative description of the city recreation system. It uses a combination of objective evaluation and subjective evaluation, the form of index to reflect the environment of a city’s leisure, leisure conditions, and leisure and economic development of standards and public awareness of urban leisure awareness. This integrated evaluation procedure is aimed at yielding appropriate and reasonable rank and value of leisure evaluation. We also give empirical examples to illustrate the techniques and how to evaluate the city leisure index. Result shows that fuzzy statistical analysis with soft computation is tending to be more realistic and reasonable in the city leisure index evaluation.
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References
T. Chen, M. Wang, Forecasting methods using fuzzy concepts. Fuzzy Sets Syst. 105, 339–352 (1999)
S-M. Chen, S-J. Niou, Fuzzy multiple attributes group decision-making based on fuzzy induced OWA operators. Expert Syst Appl. 38, 4097–4108 (2011)
J. Jun, G.T. Kyle, S.P. Vlachopulos, N.D. Theodorakis, J.D. Absher, W.E. Hammitt, Reassessing the structure of enduring leisure involvement. Leisure Sci. 34, 1–18 (2012)
J.J. LaMondia, C.R. Bhat, A conceptual and methodological framework of leisure activity loyalty accommodating the travel context. Transportation 39, 321–349 (2012)
H. Nguyen, B. Wu, Fundamentals of Statistics with Fuzzy Data (Springer, Heidelberg New York, 2006)
B. Wu, Shadows of Fuzzy Sets-A natural Way to Describe 2-D and Multi-D Fuzzy Uncertainty in Linguistic Terms, Proceedings of the 2000 FUZZ-IEEE, (2000)
B. Wu, Y-Y. Hsu, A New approach of bivariate fuzzy time series: with applications to the stock index forecasting. Int. J. Uncertainty, Fuzziness and Knowledge-based Systems 11(6), 671–690 (2004a)
B. Wu, Y-Y. Hsu, The use of kernel set and sample memberships in the identification of nonlinear time series. Soft Comput. J. 8, 207–216 (2004b)
B. Wu, C. Sun, Interval-valued statistics, fuzzy logic, and their use in computational semantics. J. Intell. Fuzzy Syst. 11, 1–7 (2001)
B. Wu, N. Tseng, A new approach to fuzzy regression models with application to business cycle analysis. Fuzzy Sets Syst. 130, 33–42 (2002)
C.T. Yeh, Weighted semi-trapezoidal approximations of fuzzy numbers. Fuzzy Sets Syst. 165, 61–80 (2011)
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Tienliu, T., Hsu, YY., Wu, B., Lai, W. (2014). Evaluating City Leisure Index with Soft Computing Methods. In: Watada, J., Xu, B., Wu, B. (eds) Innovative Management in Information and Production. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4857-0_21
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DOI: https://doi.org/10.1007/978-1-4614-4857-0_21
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