High Order Lambda Measure Based Choquet Integral Composition Forecasting Model

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.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 3111-3114
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.3111
• Online since: January 2013
• Authors: Hsiang Chuan Liu, Wei Sung Chen, Ben Chang Shia, Chia Chen Lee, Shang Ling Ou, Yih Chang Ou, Chih Hsiung Su
• Keywords: Choquet Integral, Composition Forecasting Model, Extensional Lambda Measure, Fuzzy Measure, High Order Extensional Lambda Measure

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