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Revised:August 09, 2010
Revised:August 09, 2010
中文摘要: 通过分析文化信息资源共享工程的组成和影响因素，人工神经网络系统的主要功能及实现方法，分别构建了信息资源收集整合和网络搭建的神经网络数值方程。分析研究了各种分级中心共享模式的特点，确立了以省级为超级中心，以市级为附属中心的最优共享模式。
Abstract:Neural networks numerical equations of collecting/integrating and ntework founding were established respectively via analyzing the components and influencing factors of cultural information resources sharing project, main functions and implementation methods of artificial neural network. The features of various classified conter sharing modle were analyzed and researched respectively. The optimal sharing modle established in the paper is provincial scale as the super conters and city level as affiliated conters.
keywords: neural network information resources collecting/integrating ntework founding sharing modle optimization
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引用文本：
张海波,郭祖龙,董超.基于神经网络系统实现文化信息资源共享.计算机系统应用,2011,20(2):57-60,148
ZHANG Hai-Bo,GUO Zu-Long,DONG Chao.Implementation of the Sharing of Cultural Information Resources Based on Neural Network System.COMPUTER SYSTEMS APPLICATIONS,2011,20(2):57-60,148
张海波,郭祖龙,董超.基于神经网络系统实现文化信息资源共享.计算机系统应用,2011,20(2):57-60,148
ZHANG Hai-Bo,GUO Zu-Long,DONG Chao.Implementation of the Sharing of Cultural Information Resources Based on Neural Network System.COMPUTER SYSTEMS APPLICATIONS,2011,20(2):57-60,148
