基于生态大数据的信息物理融合系统语义模型分析关键技术研究

Effectively considering the uncertain characteristics of the existing ecological monitoring data and the constraint problem of the computing environment, Research on the key technology of semantic model and analysis for combined uncertainty calculation model and theory, big data technology, ontology technology research on ecological monitoring physical fusion system, and further in-depth study based on field semantics driven massive, multidimensional and dynamic information model and uncertainty theory. The specific contents include: Research on the architecture and semantic model of ecological information physical fusion system; The multi source heterogeneous knowledge fusion mechanism of the semantic information physical fusion system. Research on the credibility analysis mechanism based on the semantic information physical fusion system; A semantic analysis prototype system based on domain data is established to prove and verify the effectiveness of the new theory and method..Meanwhile, making full use of existing data resources, this project can provide data support for CPS fields, to realize the high sharing of ecological data, solve the problem of Information Island and improve the real time, intelligence, reliability and predictability of the ecological monitoring system. This project has important practical significance and social and economic benefits in the assessment and protection of the ecological health of Three Rivers Sources with high altitude and dangerous terrain method. Meanwhile, making full use of existing data resources, this project can provide data support for CPS fields, to realize the high sharing of ecological data, solve the problem of Information Island and improve the real time, intelligence, reliability and predictability of the ecological monitoring system. This project has important practical significance and social and economic benefits in the assessment and protection of the ecological health of Three Rivers Sources with high altitude and dangerous terrain.

本项目有效地考虑现有生态监控大数据的不确定性特征和计算环境的制约问题，拟结合不确定性计算模型与理论、大数据技术、本体语义等技术研究生态监测物理融合系统的语义模型与分析的关键技术研究,同时进一步地深入研究处理基于领域语义驱动的海量、多维、动态信息的不确定性模型与理论。具体内容包括：生态信息物理融合语义模型及其融合技术的研究；基于语义信息物理融合系统的可信性分析机制研究；可信融合计算的不确定性数学理论及其定性分析应用模型研究；建立一个基于领域数据的语义分析原型系统，证明和验证新理论和方法的有效性。充分利用现有的数据资源，为CPS在三江源生态监控应用中提供良好的数据支持，实现领域生态数据的高度共享和服务，解决信息孤岛问题，提高生态监测系统的实时性、智能性、可靠性及可预测性。该项目为三江源智慧生态监控系统提供理论基础和技术保障，对三江源生态健康评估和保护具有重要的现实意义和社会经济效益。

本项目有效地考虑现有生态监控大数据的不确定性特征和计算环境的制约问题，拟结合不确定性计算模型与理论、大数据技术、本体语义等技术研究生态监测物理融合系统的语义模型与分析的关键技术研究,同时进一步地深入研究处理基于领域语义驱动的海量、多维、动态信息的不确定性模型与理论。具体内容包括：生态信息物理融合语义模型及其融合技术的研究；基于语义信息物理融合系统的可信性分析机制研究；可信融合计算的不确定性数学理论及其定性分析应用模型研究；进一步证明和验证新理论和方法的有效性，建立一个基于语义CPS的生态远程监测原型系统并应用验证，为CPS在三江源生态监控应用中提供良好的数据支持，实现领域生态数据的高度共享和服务，提高生态监测系统的实时性、智能性、可靠性及可预测性。该项目为三江源智慧生态监控系统提供理论基础和技术保障，对三江源生态健康评估和保护具有重要的现实意义和社会经济效益。