A fractional-order multivariable grey model and its application in predicting pollution emissions

The dissemination and utilization of information has been facilitated by the rapid development of the Internet. Pollution emissions should be attracted attention, and information technology can promote the effective analysis of pollution discharge. A novel enhanced model is proposed by incorporating fractional order, power exponential, linear correction, and random disturbance terms into the GM (1,N) model. By introducing the fractional-order accumulation, the model is able to capture the dynamic changes in the raw data, thereby enhancing the accuracy of models. In addition, the unknown informations in the raw data can be taken into account. The uncertainties can also be addressed in the system, which making the predictions more reliable. At last, the FMGM (1, N) model achieved high accuracy in predicting pollution emissions for Beijing and Hubei Province.