Abstract
In this study, based on the Choquet integral with respect to complete extensional L-measure and M-density, a novel composition forecasting model which composed the time series model , the exponential smoothing model and GM(1,1) forecasting model was proposed. For evaluating this improved composition forecasting model, an experiment with the data of the grain production in Jilin during 1952 to 2007 by using the sequential mean square error was conducted. Based on the M-density and N- density, the performances of Choquet integral composition forecasting model with the completed extensional L-measure, extensional L-measure, L-measure, Lambda-measure and P-measure, respectively, a ridge regression composition forecasting model and a multiple linear regression composition forecasting model and the traditional linear weighted composition forecasting model were compared. The experimental results showed that the Choquet integral composition forecasting model with respect to the completed extensional L-measure and M-density outperforms other ones. Furthermore, for each fuzzy measure, including the completed extensional L-measure, extensional L-measure, L-measure, Lambda-measure and P-measure, respectively, the Choquet integral composition forecasting model based on M-density is better than the one based on N-density.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Bates, J.M., Granger, C.W.J.: The Combination of Forecasts. Operations Research Quarterly 4, 451–468 (1969)
Zhang, H.-Q., Wang, B., Gao, L.-B.: Application of Composition Forecasting Model in the Agricultural Economy Research. Journal of Anhui Agri. Sci. 36(22), 9779–9782 (2008)
Hsu, C.-C., Chen, C.-Y.: Applications of improved grey prediction model for power demand forecasting. Energy Conversion and Management 44, 2241–2249 (2003)
Kayacan, E., Ulutas, B., Kaynak, O.: Grey system theory-based models in time series prediction. Expert Systems with Applications 37, 1784–1789, (2010)
Hoerl, A.E., Kenard, R.W., Baldwin, K.F.: Ridge regression: Some simulation. Communications in Statistics 4(2), 105–123 (1975)
Liu, H.-C., Tu, Y.-C., Lin, W.-C., Chen, C.C.: Choquet integral regression model based on L-Measure and γ-Support. In: Proceedings of 2008 International Conference on Wavelet Analysis and Pattern Recognition (2008)
Liu, H.-C.: Extensional L-Measure Based on any Given Fuzzy Measure and its Application. In: Proceedings of 2009 CACS International Automatic Control Conference, November 27-29, pp. 224–229. National Taipei University of Technology, Taipei Taiwan (2009)
Liu, H.-C.: A theoretical approach to the completed L-fuzzy measure. In: Proceedings of 2009 International Institute of Applied Statistics Studies (IIASS), 2nd Conference, Qindao, China, July 24-29 (2009)
Liu, H.-C., Ou, S.-L., Cheng, Y.-T., Ou, Y.-C., Yu, Y.-K.: A Novel Composition Forecasting Model Based on Choquet Integral with Respect to Extensional L-Measure. In: Proceedings of the 19th National Conference on Fuzzy Theory and Its Applications (2011)
Liu, H.-C., Ou, S.-L., Tsai, H.-C., Ou, Y.-C., Yu, Y.-K.: A Novel Choquet Integral Composition Forecasting Model Based on M-Density. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ACIIDS 2012, Part I. LNCS, vol. 7196, pp. 167–176. Springer, Heidelberg (2012)
Choquet, G.: Theory of capacities. Annales de l’Institut Fourier 5, 131–295 (1953)
Wang, Z., Klir, G.J.: Fuzzy Measure Theory. Plenum Press, New York (1992)
Sugeno, M.: Theory of fuzzy integrals and its applications. Unpublished doctoral dissertation, Tokyo Institute of Technology, Tokyo, Japan (1974)
Zadeh, L.A.: Fuzzy Sets as a Basis for Theory of Possibility. Fuzzy Sets and Systems 1, 3–28 (1978)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Liu, HC. (2013). A Novel Choquet Integral Composition Forecasting Model for Time Series Data Based on Completed Extensional L-Measure. In: Pedrycz, W., Chen, SM. (eds) Time Series Analysis, Modeling and Applications. Intelligent Systems Reference Library, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33439-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-33439-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33438-2
Online ISBN: 978-3-642-33439-9
eBook Packages: EngineeringEngineering (R0)