知识图中场景分析的并行世界框架

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE DataCentric Engineering Pub Date : 2020-07-14 DOI:10.1017/dce.2020.6
A. Eibeck, A. Chadzynski, Mei Qi Lim, K. Aditya, Laura Ong, A. Devanand, G. Karmakar, S. Mosbach, Raymond Lau, I. Karimi, Eddy Y. S. Foo, M. Kraft
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引用次数: 22

摘要

摘要本文提出了一种在时变知识图中模拟复杂系统的并行世界框架,并将其应用于新加坡裕廊岛的电网。底层建模系统基于语义Web堆栈。它的链接数据层是通过本体论来描述的,本体论跨越多个领域。该框架旨在允许对假设场景进行通用模拟,即使是针对复杂、互连、跨域的应用程序,也可以对系统内的复杂上层结构进行多尺度优化。该框架引入的并行世界容器确保了跨各种域边界的结构的数据分离和版本控制。属于世界特定版本的操作的分离由场景代理负责。它封装了对数据的操作功能,并充当对知识图上操作的所有其他代理的并行世界代理。以碳税的电网优化为例进行了论证。该框架允许通过改造不同类型的发电机并相应地优化电网,对与设定的碳税值相对应的电网进行建模和评估。该用例显示了使用该解决方案作为大规模CO2减排建模和规划工具的可能性,因为其具有分布式架构。影响陈述本文中开发的方法允许模拟由许多相互依存的部分组成的复杂系统,如工业园区及其变体,称为平行世界。除了考虑不同场景的能力外,我们的方法的一个关键区别特征是采用了知识图和自主软件代理,该方法基于通用通用设计,能够实现异构软件之间的互操作性,从而实现跨领域应用程序之间的互互操作性。因此,这里提出的方法允许城市规划者和政策制定者提出假设问题或探索替代方案——这一过程可以在决策中发挥重要作用。例如,针对两个不同级别的碳税,考虑优化新加坡裕廊岛的电网,从而展示了该方法如何有助于减少碳足迹的规划。
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A Parallel World Framework for scenario analysis in knowledge graphs
Abstract This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture. Impact Statement The methodology developed in this paper allows simulation of complex systems that consist of many interdependent parts, such as an industrial park, as well as variations thereof, referred to as parallel worlds. In addition to the ability to consider different scenarios, a key distinguishing feature of our approach, which is based on a generic all-purpose design that enables interoperability between heterogeneous software and, as a consequence, cross-domain applications, is its employment of knowledge graphs and autonomous software agents. As such, the methodology presented here allows city planners and policy makers to ask what-if questions or explore alternatives—a process that can play an important role in decision-making. As an example, optimizing the electrical grid of Jurong Island in Singapore is considered, for two different levels of carbon tax, thus demonstrating how the methodology can assist planning for carbon footprint reduction.
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
期刊最新文献
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