摘要
为了有效地测度区域产业集群升级进程,识别预判潜在问题。考虑物流业为代表的生产性服务业在区域产业集群升级中的作用,在系统分析区域产业集群升级特征的基础上,构建基于经济学投入产出视角的特征指标体系,并提出区域产业集群升级进程测度识别框架模型。进一步,以重庆地区产业集群升级为例,基于人工神经网络与遗传算法相结合的方法模拟和仿真该区域产业集群一定周期内升级进程中各特征指标的演进趋势,并与已完成产业集群升级地区横向对比,分析其所处的阶段、时间窗口及潜在的问题,以期为该地区产业集群升级提供指导。
In order to effectively measure and identify the different stages and potential problems in upgrading process of the regional industrial cluster,the importance of the producer services represented by logistics industry in the upgrading process is considered,and the index system composed of economic inputs and outputs on the basis of the systematic analysis of upgrading's features in the regional industrial cluster is built,then the framework of identification for upgrading's process about the regional industry cluster is proposed. Furthermore,giving an example of the industrial cluster in Chongqing areas,the method which is on the basis of combination of artificial neural network and genetic algorithm is used for simulating the evolutional tendency of all characteristic indexes of the regional industrial cluster during constant promotion period,and compares the results with those obtained from other completed upgrading transversely to analyze the stages,time windows and potential problems and to provide instructions for the promotion of this regional industrial cluster.
出处
《物流工程与管理》
2017年第9期106-112,共7页
Logistics Engineering and Management
基金
国家自然科学基金资助项目(No.71401019)
重庆市社会科学规划项目(2014QNGL47)
重庆市教委科学技术项目(No.KJ1600508)
重庆市基础科学与前沿技术研究项目(No.cstc2017jcyj AX0170)
关键词
产业集群
产业升级
识别与预测
BPNN-GA算法
生产性服务业
industrial cluster
industrial upgrading
identification and forecast
BPNN-GA algorithm
producer services
