Nonlinear combined forecasting model based on fuzzy adaptive variable weight and its application |
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| Authors: | Ai-hua Jiang Chi Mei Jia-qiang E and Zhang-ming Shi |
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| Affiliation: | [1]School of Energy Science and Engineering, Central South University, Changsha 410083, China [2]College of Mechanical and Automotive Engineering, Hunan University, Changsha 410082, China [3]Hunan Research Center of Energy-Saving Evaluation Technology, Central South University, Changsha 410083, China |
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| Abstract: | In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system, a new nonlinear
fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error, the
change tendency of the forecasted object, gray basic weight and adaptive control coefficient on the basis of the method of
fuzzy variable weight. Based on Visual Basic 6.0 platform, a fuzzy adaptive variable weight combined forecasting and management
system was developed. The application results reveal that the forecasting precisions from the new nonlinear combined forecasting
model are higher than those of other single combined forecasting models and the combined forecasting and management system
is very powerful tool for the required decision in complex industry system. |
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| Keywords: | nonlinear combined forecasting nonlinear time series method of fuzzy adaptive variable weight relative error adaptive control coefficient |
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