Affiliation:
1. School of Landscape Architecture, Zhejiang Agriculture and Forest University, Hangzhou, Zhejiang Province, PR of China
2. Suzhou World Cultural Heritage Classical Garden Protection and Supervision Center, Suzhou, Jiangsu Province, PR of China
Abstract
Taking garden heritage ontologies as the object, this paper explores monitoring and early-warning methods of heritage based on fuzzy cluster analysis. A monitoring and early-warning system for garden heritage ontologies is designed and consists of monitoring indexes, a monitoring program, monitoring data collection, application of an early-warning grading evaluation model and conclusion of early-warning grading. Taking the Suzhou classical garden heritage as an example, it can be concluded that the systematic method can integrate various qualitative and quantitative index values and collectively reflect the overall state of garden heritage ontologies as well as match a heritage monitoring ontology with an early warning grade by calculating the data similarity matrix, membership matrix, fuzzy similarity matrix, fuzzy equivalent matrix and cut matrix. Five kinds of heritage ontologies with a total of twenty-seven heritage monitoring indicators are applied in the model and then be matched with MATLAB software to obtain accurate early-warning results. When types of heritage ontology need to be expanded, the heritage is further refined, or the heritage is more comprehensive, this method is applicable.
Publisher
Vilnius Gediminas Technical University
Subject
Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Environmental Engineering
Cited by
3 articles.
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