A new multivariable grey prediction model with structure compatibility |
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| Institution: | 1. College of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China;2. Collaborative Innovation Center for Chongqing‘s Modern Trade Logistics & Supply Chain, Chongqing Technology and Business University, Chongqing 400067, China;3. College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;1. College of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China;2. School of Economics and Management, Chongqing Normal University, Chongqing 401331, China;3. School of Science, Southwest University of Science and Technology, Mianyang 621010, China |
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| Abstract: | A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and multivariable grey prediction models by adjusting and changing the model's parameters. To test the performance of the new model, three case studies were performed. The simulation and prediction results of the new model were compared with those of other grey prediction models. Results showed that the new model had evidently superior performance to other grey models, which confirms that the structure design of the new model is more reasonable than those of the other existing grey prediction models. |
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