文献类型：期刊文献

英文题名：A combinatorial method based on machine learning algorithms for enhancing cultural economic value

作者：Qi, Yuqing[1]; Ren, Wei[2]; Shi, Meiyu[3]; Liu, Qinyun[4]

第一作者：齐宇清

通讯作者：Shi, Meiyu

机构：[1] College of Arts, Beijing Union University, Beijing, 100101, China; [2] UNESCO World Heritage Institute of Training and Research-Asia and Pacific [Shanghai], Tongji University, Shanghai, 200092, China; [3] Center for Faculty Development, Beijing Union University, Beijing, 100101, China; [4] Centre for Creative Computing, Bath Spa University, BA2 9BN, United Kingdom

第一机构：北京联合大学艺术学院

年份：2020

卷号：16

期号：7

起止页码：1105-1117

外文期刊名：International Journal of Performability Engineering

收录：EI(收录号：20203609127854);Scopus(收录号：2-s2.0-85090040296)

基金：This work was supported in part by Open Projects Fund of Key Laboratory of Ecology and Energy-saving Study of Dense Habitat (Tongji University), Ministry of Education (Grant No.201820302 201820302) and Natural Science Foundation of China (Grant no. 71473018) and the Project of Beijing Union University, Beijing, China (Grant no. BPHR2019DS07).

语种：英文

外文关键词：Backpropagation - Computation theory - Tourism

摘要：Cultural heritage is created by people all around the world in a long history. Heritage sites connect with normal people on the tourism aspect and present close relationships with people's normal life. However, some problems have appeared in the cultural heritage sites' establishment process, such as being over commercialised, over developed, and damaging the nature. To maintain the balance between human living and nature and improve the cultural heritage popularity, work should be done with all available technologies, like AI and Creative Computing. AI can be used for supervising the cultural heritage area for the protection aim. The back propagation neural network is used in this research for supervising and protecting the heritage site. Meanwhile, the cultural heritage tourism value is a kernel index to evaluate people's interest in the heritage. To enhance the popularity of cultural heritage, improving the tourism value of cultural heritage is required. As artificial intelligence can complete complex data analysis, the cultural heritage value elements can be fully explored by this method. The tourism elements of the cultural heritage can be expanded with the associated learning algorithm connected with public databases. Novel elements could be discovered, for example by attempting different combinations of heritages. Based on Boden's theory, the transformational method can achieve creativity. Therefore, traditional elements can be replaced by novel elements to generate new tourism element sets that can be applied in the cultural heritage sites. Then, creative computing theories are used for combining computer techniques and tourism activities to complete the cultural heritage protection and tourism value improvement. Furthermore, the performability of this approach is considered as imperative characteristics during the approach generation process. Achieving sustainability and dependability are necessary for the approach (or services, systems and so forth) application in target realms. The entire workflow of this approach for evaluating tourism value and identifying novel fusions among tourism elements has positive influences on approach performance. A system could be developed based on this approach, which would have stable outputs for improving tourism values. ? 2020 Totem Publisher, Inc. All rights reserved.