基于BP神经网络的创意产业集群知识互补度评价

Li Yu-hua, Tan Jin-yan, Hu Yao-ying
{"title":"基于BP神经网络的创意产业集群知识互补度评价","authors":"Li Yu-hua, Tan Jin-yan, Hu Yao-ying","doi":"10.1109/ICMSE.2011.6069940","DOIUrl":null,"url":null,"abstract":"Creative industries are intelligent, highly knowledgeable. Cluster model increasingly becomes the main economic organization form of the world creative industry. Getting complementary knowledge and realizing the knowledge complementary within creative industry cluster is the main motivation of each cooperator. What's more, the complementary degree of knowledge also determines the development altitude of creative industry cluster. So, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. This paper constructs the creative industry cluster evaluation index system of knowledge complementary degree. Simultaneously, the paper has proposed the method to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is a model without linear mapping. It can give a satisfactory effort while the indices with a high level of correlation, nonlinear changing and data lacking. So, it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.","PeriodicalId":280476,"journal":{"name":"2011 International Conference on Management Science & Engineering 18th Annual Conference Proceedings","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of knowledge complementary degree for creative industry cluster based on BP neural networks\",\"authors\":\"Li Yu-hua, Tan Jin-yan, Hu Yao-ying\",\"doi\":\"10.1109/ICMSE.2011.6069940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Creative industries are intelligent, highly knowledgeable. Cluster model increasingly becomes the main economic organization form of the world creative industry. Getting complementary knowledge and realizing the knowledge complementary within creative industry cluster is the main motivation of each cooperator. What's more, the complementary degree of knowledge also determines the development altitude of creative industry cluster. So, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. This paper constructs the creative industry cluster evaluation index system of knowledge complementary degree. Simultaneously, the paper has proposed the method to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is a model without linear mapping. It can give a satisfactory effort while the indices with a high level of correlation, nonlinear changing and data lacking. So, it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.\",\"PeriodicalId\":280476,\"journal\":{\"name\":\"2011 International Conference on Management Science & Engineering 18th Annual Conference Proceedings\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Management Science & Engineering 18th Annual Conference Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMSE.2011.6069940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Management Science & Engineering 18th Annual Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSE.2011.6069940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

创意产业是智慧的,知识丰富的。集群模式日益成为世界创意产业的主要经济组织形式。获取知识互补,实现创意产业集群内部的知识互补是各合作主体的主要动机。此外,知识的互补程度也决定了创意产业集群的发展高度。为此,应用BP神经网络模型对创意产业集群内部的知识互补程度进行评价。本文构建了创意产业集群知识互补度评价指标体系。同时,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。研究表明,BP神经网络是一个没有线性映射的模型。对于相关性高、非线性变化和数据缺乏的指标,该方法能给出满意的结果。因此,它是一种较为理想的预测方法,适用范围广,具有较高的推广价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of knowledge complementary degree for creative industry cluster based on BP neural networks
Creative industries are intelligent, highly knowledgeable. Cluster model increasingly becomes the main economic organization form of the world creative industry. Getting complementary knowledge and realizing the knowledge complementary within creative industry cluster is the main motivation of each cooperator. What's more, the complementary degree of knowledge also determines the development altitude of creative industry cluster. So, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. This paper constructs the creative industry cluster evaluation index system of knowledge complementary degree. Simultaneously, the paper has proposed the method to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is a model without linear mapping. It can give a satisfactory effort while the indices with a high level of correlation, nonlinear changing and data lacking. So, it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信