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Functional ontologies and their application to hydrologic modeling: Development of an integrated semantic and procedural knowledge model and reasoning engine.

机译:功能本体及其在水文建模中的应用:集成的语义和过程知识模型以及推理引擎的开发。

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摘要

This dissertation represents the research and development of new concepts and techniques for modeling the knowledge about the many concepts we as hydrologists must understand such that we can execute models that operate in terms of conceptual abstractions and have those abstractions translate to the data, tools, and models we use every day. This hydrologic knowledge includes conceptual (i.e. semantic) knowledge, such as the hydrologic cycle concepts and relationships, as well as functional (i.e. procedural) knowledge, such as how to compute the area of a watershed polygon, average basin slope or topographic wetness index.;This dissertation is presented as three papers and a reference manual for the software created. Because hydrologic knowledge includes both semantic aspects as well as procedural aspects, we have developed, in the first paper, a new form of reasoning engine and knowledge base that extends the general-purpose analysis and problem-solving capability of reasoning engines by incorporating procedural knowledge, represented as computer source code, into the knowledge base. The reasoning engine is able to compile the code and then, if need be, execute the procedural code as part of a query. The potential advantage to this approach is that it simplifies the description of procedural knowledge in a form that can be readily utilized by the reasoning engine to answer a query. Further, since the form of representation of the procedural knowledge is source code, the procedural knowledge has the full capabilities of the underlying language. We use the term "functional ontology" to refer to the new semantic and procedural knowledge models. The first paper applies the new knowledge model to describing and analyzing polygons.;The second and third papers address the application of the new functional ontology reasoning engine and knowledge model to hydrologic applications. The second paper models concepts and procedures, including running external software, related to watershed delineation. The third paper models a project scenario that includes integrating several models. A key advance demonstrated in this paper is the use of functional ontologies to apply metamodeling concepts in a manner that both abstracts and fully utilizes computational models and data sets as part of the project modeling process.
机译:本论文代表了新概念的研究和开发,这些模型和技术用于对水文学家必须理解的许多概念的知识进行建模,以便我们可以执行以概念抽象的方式运行的模型,并将这些抽象转换为数据,工具和方法。我们每天使用的模型。这些水文知识包括概念性(即语义)知识,例如水文循环概念和关系,以及功能性(即程序性)知识,例如如何计算流域多边形的面积,平均流域坡度或地形湿度指数。 ;本文以三篇论文和所创建软件的参考手册的形式呈现。由于水文知识既包括语义方面也包括程序方面,因此我们在第一篇论文中开发了一种新形式的推理引擎和知识库,通过结合程序知识扩展了推理引擎的通用分析和解决问题的能力(表示为计算机源代码)进入知识库。推理引擎能够编译代码,然后在需要时执行过程代码作为查询的一部分。这种方法的潜在优势在于,它以一种易于被推理引擎用来回答查询的形式简化了过程知识的描述。此外,由于过程知识的表示形式是源代码,因此过程知识具有基础语言的全部功能。我们使用术语“功能本体”来指代新的语义和过程知识模型。第一篇论文将新的知识模型应用于多边形的描述和分析。第二篇和第三篇论文论述了新的功能本体推理引擎和知识模型在水文应用中的应用。第二篇论文对与分水岭划定有关的概念和程序(包括运行外部软件)进行了建模。第三篇论文对包括集成多个模型的项目方案进行了建模。本文所展示的一个关键进展是使用功能本体以一种抽象和充分利用计算模型和数据集作为项目建模过程一部分的方式来应用元建模概念。

著录项

  • 作者

    Byrd, Aaron Range.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Artificial Intelligence.;Hydrology.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 189 p.
  • 总页数 189
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:41:14

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