摘要
针对我国区域"两化融合"水平量化问题,提出了基于粗糙集和神经网络的区域两化融合水平评价模型。首先构建了区域两化融合指标体系,然后,运用粗糙集进行属性约简,进而运用神经网络模型评价各地区区域两化融合水平。我国区域两化融合水平实证结果表明:基于粗糙集和神经网络模型的区域两化融合评价模型较为合理,具有很好的泛化能力。
As for quantification of China＇s regional integration of information and industrialization ,this paper propose a eval-uation model of integration of regional information and industrialization based on rough set and neural network .Firstly ,an evaluation indicators system of China＇s integration of regional information and industrialization was constructed ;then the rough set is used for attribute reduction ;finally ,neural network is used to evaluate level of China＇s regional integration of information and industrialization .Empirical study results based on China＇s related data show that the proposed evaluation model based on rough set and neural network is more reasonable and with good generalization ability ;the proposed model can provide decision-making reference for regional to promote integration of information and industrialization .
出处
《科技进步与对策》
CSSCI
北大核心
2014年第9期125-129,共5页
Science & Technology Progress and Policy
基金
国家自然科学基金项目(71071003
71272164)
国家教育部人文社会科学研究规划基金项目(10YJA630031)
关键词
两化融合水平
评价指标
粗糙集
神经网络模型
Integration Of Information and Industrialization
Evaluation Indicators
Rough Set
Neural Network Model
