区域经济发展潜力预测模型仿真研究

发布时间：2018-02-24 17:00

本文关键词： 区域经济发展潜力数据挖掘预测支持向量机决策域　出处：《计算机仿真》2013年09期 　论文类型：期刊论文

【摘要】：区域经济潜力受到实体过多、经济结构动态变动大的影响,变动比例具有较强的非线性,不同的影响指标间存在信息冗余和信息干扰,导致传统的经济潜力发展预测方法获取的预测结果受到这种突变性的影响,存在局部最优的问题,造成较大的误差。提出一种决策域观念的区域经济发展潜力预测模型。采用传统的支持向量机解决区域经济影响指标的非线性特征,获取原始的经济预测数据,在决策过程中,引入决策域方法构建训练经济相关数据集的决策域,再对决策域进行剪枝处理,把决策域转化为标准决策数据,依据这些标准数据对新的区域经济影响指标进行分类,最终获取完整的区域经济预测数据。实验结果说明,改进模型同其它预测模型相比,具备更高的区域经济预测准确率,能够快速准确的预测出相关区域经济发展的潜力趋势,具有重要的应用价值。
[Abstract]:The potential of regional economy is affected by too many entities and large dynamic changes in economic structure. The ratio of change is nonlinear, and there is information redundancy and information interference among different impact indicators. As a result of this sudden change, the prediction results obtained by the traditional forecasting methods of economic potential development are subject to the problem of local optimum. This paper presents a prediction model of regional economic development potential based on the concept of decision domain. The traditional support vector machine is used to solve the nonlinear characteristics of regional economic impact indicators, and the original economic prediction data are obtained. This paper introduces the decision domain method to construct the decision domain of the relevant data set of training economy, then prunes the decision domain, converts the decision domain into the standard decision data, and classifies the new regional economic impact index according to these standard data. Finally, complete regional economic forecasting data are obtained. The experimental results show that compared with other forecasting models, the improved model has higher prediction accuracy and can quickly and accurately predict the potential trend of regional economic development. It has important application value.
【作者单位】：河北经贸大学外语教学部;
【分类号】：O242.1;F061.5

【参考文献】