High order lambda measure based choquet integral composition forecasting model

Hsiang Chuan Liu, Wei Sung Chen, Ben Chang Shia, Chia Chen Lee, Shang Ling Ou, Yih Chang Ou, Chih Hsiung Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a novel fuzzy measure, high order lambda measure, was proposed, based on the Choquet integral with respect to this new measure, a novel composition forecasting model which composed the GM(1,1) forecasting model, the time series model and the exponential smoothing model was also proposed. For evaluating the efficiency of this improved composition forecasting model, an experiment with a real data by using the 5 fold cross validation mean square error was conducted. The performances of Choquet integral composition forecasting model with the P-measure, Lambda-measure, L-measure and high order lambda 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 high order lambda measure has the best performance.

Original languageEnglish
Title of host publicationApplied Mechanics and Materials
Pages3111-3114
Number of pages4
Volume284-287
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012 - Kaohsiung, Taiwan
Duration: Nov 2 2012Nov 6 2012

Publication series

NameApplied Mechanics and Materials
Volume284-287
ISSN (Print)16609336
ISSN (Electronic)16627482

Other

Other2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012
CountryTaiwan
CityKaohsiung
Period11/2/1211/6/12

Fingerprint

Chemical analysis
Linear regression
Mean square error
Time series
Experiments

Keywords

  • Choquet integral
  • Composition forecasting model
  • Extensional lambda measure
  • Fuzzy measure
  • High order extensional lambda measure

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Liu, H. C., Chen, W. S., Shia, B. C., Lee, C. C., Ou, S. L., Ou, Y. C., & Su, C. H. (2013). High order lambda measure based choquet integral composition forecasting model. In Applied Mechanics and Materials (Vol. 284-287, pp. 3111-3114). (Applied Mechanics and Materials; Vol. 284-287). https://doi.org/10.4028/www.scientific.net/AMM.284-287.3111

High order lambda measure based choquet integral composition forecasting model. / Liu, Hsiang Chuan; Chen, Wei Sung; Shia, Ben Chang; Lee, Chia Chen; Ou, Shang Ling; Ou, Yih Chang; Su, Chih Hsiung.

Applied Mechanics and Materials. Vol. 284-287 2013. p. 3111-3114 (Applied Mechanics and Materials; Vol. 284-287).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, HC, Chen, WS, Shia, BC, Lee, CC, Ou, SL, Ou, YC & Su, CH 2013, High order lambda measure based choquet integral composition forecasting model. in Applied Mechanics and Materials. vol. 284-287, Applied Mechanics and Materials, vol. 284-287, pp. 3111-3114, 2nd International Conference on Engineering and Technology Innovation 2012, ICETI 2012, Kaohsiung, Taiwan, 11/2/12. https://doi.org/10.4028/www.scientific.net/AMM.284-287.3111
Liu HC, Chen WS, Shia BC, Lee CC, Ou SL, Ou YC et al. High order lambda measure based choquet integral composition forecasting model. In Applied Mechanics and Materials. Vol. 284-287. 2013. p. 3111-3114. (Applied Mechanics and Materials). https://doi.org/10.4028/www.scientific.net/AMM.284-287.3111
Liu, Hsiang Chuan ; Chen, Wei Sung ; Shia, Ben Chang ; Lee, Chia Chen ; Ou, Shang Ling ; Ou, Yih Chang ; Su, Chih Hsiung. / High order lambda measure based choquet integral composition forecasting model. Applied Mechanics and Materials. Vol. 284-287 2013. pp. 3111-3114 (Applied Mechanics and Materials).
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