基于马尔可夫模型的东北三省产业结构预测

为了合理规划东北三省产业结构，提升东北三省区域经济产业的整体竞争力，笔者应用马尔可夫预测方法对东北三省产业结构进行了研究，并用区间自适应遗传算法求解马尔可夫状态转移概率矩阵，依据2004—2014 年产业结构的统计数据，预测了东北三省第一、二、三产业结构，平均误差为2.92%，具有较高的预测精度。用该模型对2015—2016 年东北三省产业结构进行了预测，为东北三省制定相应的地方产业结构政策提供一定的理论依据。

Industrial Structure Prediction of the Three Provinces in Northeast China Based on Markov Model

In order to plan the industrial structures in the three northeastern provinces, to increase the three northeast provinces regional economic industry''s overall competitiveness, the industrial structures in the three northeastern provinces are studied by the author using Markov prediction method. And the interval adaptive genetic algorithm is employed to solve the Markov state transfer probability matrix. According to 2004-2014 statistical data of industrial structure, the first, second and third industrial structures in the three northeastern provinces are predicted. The average error is 2.92 percent. The industrial structures in the three northeastern provinces in 2015-2016 are predicted using this model, it provides a certain amount of theoretical basis for making corresponding local industrial structure policies in the three northeastern provinces.