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The reserve of crude oil in the Arctic area is abundant. Ice melting ismaking it possible to have intermediate access to the Arctic crude oil and itstransportation. A novel compositional data's grey model is proposed in thispaper to structurally forecast Arctic crude oil import. Firstly, the generalaccumulative operation sequence of multivariate compositional data is definedaccording to Aitchison geometry, then obtaining the novel model with the formof the compositional data vectors. Secondly, this paper studies the leastsquare parameter estimation of the model. The novel model is deduced andselected as the time-response expression of the solution. Thirdly, this paperinfuses the novel model with traditional grey model to improve its robustness.Differential Evolution algorithm is introduced to determine the optimal valueof the general matrix. Lastly, two validation examples are provided forconfirming the effectiveness of the novel model by comparing it with otherexisting models, before being employed to forecast the crude oil importstructure in China. The results show that the novel model provides betterperformance in all crude oil cases in short-term forecasting. Therefore, byusing the new model, China's development parameter is 0.5214 and DeterminationFactor of the novel model is 0.5999, which means that the crude oil importstructure of China is being changed. Specifically, the amount of crude oilimported from the Arctic area is obviously increasing in the next 6 years,showing sufficient proof of the edge owned by the Arctic area: abundant crudeoil reserves and shortening transportation distance.

Novel Compositional Data's Grey Model for Structurally Forecasting Arctic Crude Oil Import