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针对传统的灰色系统中预测模型涉及相关因素多,预测效率与精度不足等问题,结合粗糙集理论和支持向量回归机方法,提出了一种改进的预测优化算法。该模型算法首先利用属性约简技术解决影响因子不相容性问题并有效缩减了影响预测值的因子空间,降低计算的复杂性;然后采用灰色模型进行数据预测,并将预测结果作为支持向量机的输入,进而求解优化模型的预测值,最后采用1990～2010年我国人口数据对我国人口进行预测。实验结果表明该预测优化模型在预测效率和精度方面具有较好的表现。
Aiming at the problems of the traditional gray system prediction model, such as many related factors, the lack of prediction efficiency and accuracy, an improved prediction optimization algorithm is proposed based on rough set theory and support vector regression method. The model algorithm firstly uses the attribute reduction technique to solve the problem of influence factor incompatibility and effectively reduces the factor space that affects the prediction value and reduces the computational complexity. Then, the gray model is used to predict the data, and the prediction result is used as support vector machine , And then solve the predictive value of the optimization model. Finally, the population of our country from 1990 to 2010 is used to predict the population of China. Experimental results show that the prediction model has good performance in prediction efficiency and accuracy.