黑龙江省创意产业集群知识互补度的神经网络评价  

Neural networks evaluation of knowledge complementary degree for creative industry cluster

作　　者：胡瑶瑛[1] 李煜华[1] 谭金艳[1] 

机构地区：[1]哈尔滨理工大学管理学院,黑龙江哈尔滨150040

出　　处：《科技与管理》2012年第3期83-86,共4页Science-Technology and Management

基　　金：黑龙江省教育厅人文社会科学研究项目(12522041)

摘　　要：针对黑龙江省创意产业集群内企业选择和利用何种互补性知识更有利于促进集群知识共享与传播、加速产业机构升级的问题,采用BP神经网络模型来评价创意产业集群知识互补度,构建了创意产业集群知识互补度的评价指标体系,提出了基于BP神经网络的创意产业集群知识互补度评价方法。研究显示,BP神经网络是一种非线性映射模式,在指标间相关度较高、呈非线性变化,或数据缺漏不全等情况下仍可得出预测结果,为促进集群知识共享、传播与运用提供理论支持,并为黑龙江省创意产业集群效应的提高和创意产业结构的升级提供决策依据。Focusing on which complementary knowledge is chose and used for cluster enterprises of Heilongjiang creative industry to promote cluster knowledge sharing and dissemination and speed up the upgrade of industrialstructure, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. The creative industry cluster evaluation index system of knowledge complementary degreehas been constructed. Simultaneously,the method has been proposed to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is amodel without linear mapping. It can give the forecast result while the indices with a high level of correlation, nonlinear changing and data lacking. And, it promotes the theoretical support for the knowledge sharing, dissemination and application of creative industry cluster enterprises. It also provides the decision-making basis for the improvement of Heilongjiang creative industry cluster effect and the upgrade of Heilongjiang creative industrial structure.

关 键 词：知识互补度 黑龙江省创意产业集群 BP神经网络 评价指标体系 

分 类 号：F062.9[经济管理—政治经济学]