【作者】 胡敏； 赵春标；

【Author】 Hu Min Zhao Chunbiao (School of Computer & Information,HeFei University of Technology,Hefei Anhui 230009,China)

【机构】 合肥工业大学计算机与信息学院；

【摘要】 对现实中经济数据的预测一直是预测的难点,利用BP神经网络预测模型结合传统的预测方法构造一种加权组合模型。对影响工业经济的主要指标数据进行模拟训练与学习,并借助当年的国家发布的经济预测指标辅助加以修复。实例结果表明这种预测方法可以很大的提高预测的精度,可以更好的把握经济发展趋势,对宏观调控的智能决策提供理论和数字支撑。更多还原

【Abstract】 The early warning and forecast of economic data has been a difficult point in the economic society.The use of BP network prediction model combining with traditional economic model constructs a new weighted model.Through the simulation of learning and training on main indicators of the industrial data,this model can repair the national economic index.Through the instance,this method can improve the accuracy of the prediction and hold the trend of economic better.This method also can give a good support to the theory of intelligent decision-making and economic data.更多还原