摘要
研究小型城市GDP增长准确计算方法。在经济危机中,各行业的行业生产总数发生较大的波动,生产数量和销售数量都呈现较大的不规则变化。造成常规评估模型计算残差过大而不稳定。传统的评估模型依赖计算中的残差结果,一旦残差误差过大,将造成评估模型不稳定,导致GDP增长评估准确性降低。提出了一种支持向量机非线性回归模型的GDP增长评估方法。根据城市经济数据建立支持向量机非线性回归模型,对城市的GDP增长进行评估,通过神经网络残差修正方法对非线性回归模型中的残差进行补偿,从而实现GDP增长评估。实验结果表明,改进算法能够提高GDP增长评估的准确性。
Research the accurate calculating method of small city GDP growth. In the economic crisis, the various sectors of industry total production have great differences, production quantity and sales volume have large irregular changes, which causes conventional evaluation model not stable. The traditional evaluation model is particularly dependent on the residual results, once the residual errors are too large, the evaluation model is not stable, leading to low accurate evaluation of GDP growth. The paper put forward a support vector machine nonlinear regression model of GDP growth assessment. According to the city economic data, support vector machine nonlinear regression model was set up to calculate the city of GDP growth. And through the neural network residual correction method for nonlinear regression model of the residuals compensation, the accurate GDP growth calculation was realized. The experimental results show that this algorithm can improve the accuracy of assessment of GDP growth.
出处
《计算机仿真》
CSCD
北大核心
2013年第1期301-304,共4页
Computer Simulation
关键词
经济危机
评估模型
支持向量机
Economic crisis
Evaluation model
Support vector machine （SVM）
