Abstract
Aiming at the defect of visibility graph, this paper first proposes the definition of fuzzy visibility graph, then gives a new similarity measure of time series induced from the similarity of fuzzy visibility graphs. Based on the proposed definition and similarity measure, a novel time series forecasting method is established. To demonstrate the performance of the proposed method, experiments are carried out on Alabama enrollment, stock price index and Shanghai Pudong Development Bank’s closing price. The results show that the proposed method improves the accuracy of prediction.
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References
Tiwari, A.K., Suresh, K.G., Arouri, M., Teulon, F.: Causality between consumer price and producer price: evidence from Mexico. Econ. Model. 36, 432–440 (2014)
Wang, D., Podobnik, B., Horvatić, D., Stanley, H.E.: Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices. Phys. Rev. E 83(4), 046121 (2011)
Brown, R.G.: Exponential Smoothing for Predicting Demand. Operations Research, vol. 5, p. 145. Institute for Operations Research and the Management Sciences, Linthicum (1957)
Box, G., Jenjins, G.: Time Series Analysis, Forecasting and Control. Holden-Day (1970)
Brown, R.G.: Statistical forecasting for inventory control. J. Roy. Stat. Soc. 123(3) (1959)
Maguire, L.P., Roche, B., Mcginnity, T.M., et al.: Predicting chaotic time series using a fuzzy neural network. Inf. Sci. 112, 125–136 (1998)
Casdagli, M.: Nonlinear prediction chaotic time series. Phys. D 35, 335–356 (1989)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series. Part I. Fuzzy Sets Syst. 54(1), 1–9 (1993)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series. Part II. Fuzzy Sets Syst. 62(1), 1–8 (1994)
Jilani, T.A., Burney, S.M.A.: A refined fuzzy time series model for stock market forecasting. Phys. A 387(12), 2857–2862 (2008)
Zhang, H., Wei, D., Hu, Y., Lan, X., Deng, Y.: Modeling the self-similarity in complex networks based on Coulombs law. Commun. Nonlinear Sci. Numer. Simul. 35, 97–104 (2016)
Wang, S., Du, Y., Deng, Y.: A new measure of identifying influential nodes: efficiency centrality. Commun. Nonlinear Sci. Numer. Simul. 47, 151–163 (2017)
Lacasa, L., Luque, B., Ballesteros, F., et al.: From time series to complex networks: the visibility graph. Proc. Natl. Acad. Sci. U.S.A. 105(13), 4972–4975 (2008)
Zhang, R., Ashuri, B., et al.: Forecasting construction cost index based on visibility graph: a network approach. Phys. A Stat. Mech. Appl. 493, 239–252 (2017)
Wang, M., Vilela, A.L., Tian, L., et al.: A new time series prediction method based on complex network theory. In: 2017 IEEE International Conference on Big Data, pp. 4170–4175. IEEE (2018)
Zhang, R., Ashuri, B., Deng, Y.: A novel method for forecasting time series based on fuzzy logic and visibility graph. Adv. Data Anal. Classif. 11(4), 759–783 (2017)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)
Luque, B., Lacasa, L., Ballesteros, F., Luque, J.: Horizontal visibility graphs: exact results for random time series. Phys. Rev. E 80(4), 046103 (2009)
Zhou, T.T., Jin, N.D., Gao, Z.K., Luo, Y.B.: Limited penetrable visibility graph for establishing complex network from time series. Acta Phys. Sin. 61(3), 030506 (2012)
Bezsudnov, I.V., Snarskii, A.A.: From the time series to the complex networks: the parametric natural visibility graph. Phys. A 414, 53–60 (2014)
Li, X., Sun, M., Gao, C., et al.: The parametric modified limited penetrable visibility graph for constructing complex networks from time series. Phys. A 492, 1097–1106 (2018)
Acknowledgement
This work is supported by the National Natural Science Foundation of China (No. 11571001, No. 11701338).
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Zhou, J., Wang, J., Yu, F., Yu, L., Wang, X. (2020). A Novel Time Series Forecasting Method Based on Fuzzy Visibility Graph. 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 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_28
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DOI: https://doi.org/10.1007/978-3-030-32591-6_28
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