2021年山西省古遗址脆弱性评估数据

文物信息特征由文物四有档案和实地获取数据定义构建。建立“古遗址—洪涝”灾害模型，数据由机器学习、深度学习方法自动获取，准确率、精确率、召回率较高，符合行业要求。古遗址本体脆弱性、孕灾环境敏感性通过监测报告、相关文献以及网络爬虫获取，通过知识融合进行语义消歧，数据质量较好。本体脆弱性通过访问水利部网站、县志进行历史查询获取，数据来源可靠。通过水位仪、遥感影像、雨量器等仪器或数据进行监测获取，数据实时性强。所有监测指标符合古遗址洪涝灾害实际需求，监测指标体系完善。

The characteristics of cultural relics are defined and constructed based on the "Four-Specifications" archives of cultural relics and field-collected data. An "Ancient Site-Flood Disaster" model was established, where the data is automatically acquired through machine learning and deep learning methods, with high accuracy, precision and recall rates that meet industry requirements. The vulnerability of the ancient site itself and the sensitivity of disaster-prone environments are obtained via monitoring reports, relevant literature and web crawlers, and semantic disambiguation is conducted via knowledge fusion to ensure good data quality. The vulnerability of the ancient site itself is further acquired through historical inquiries by accessing the official website of the Ministry of Water Resources and local chronicles, ensuring reliable data sources. Monitoring data is collected through instruments and datasets such as water level gauges, remote sensing imagery and rain gauges, with strong real-time performance. All monitoring indicators meet the actual demands of flood disasters affecting ancient sites, and the monitoring indicator system is comprehensive and well-developed.

搜集汇总

背景与挑战

背景概述

该数据集通过机器学习和深度学习方法自动获取，构建了'古遗址-洪水'灾害模型，具有高准确性和召回率。数据来源可靠，包括监测报告、相关文献、网络爬虫等，并通过知识融合进行语义消歧，数据质量良好。