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Toward an expert system for terrain analysis.

机译:建立用于地形分析的专家系统。

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摘要

Terrain analysis is the systematic study of image patterns relating to the origin, and composition of distinct terrain units called landforms. It takes into account and provides information about physical site factors which are used by civil engineers for evaluating the suitability of a site for a terrain related engineering application. Terrain analysis is a time consuming labor intensive process and requires a significant degree of expertise. In this dissertation, an expert system paradigm has been adopted, for developing a computational approach to terrain analysis problem solving. A methodology was developed for the representation and management of uncertain terrain knowledge. The "vagueness" that is inherent in the descriptions of terrain analysis terms was represented using fuzzy models. The Dempster-Shafer theory of evidence was adopted to establish hypotheses about the type of terrain based on observed evidences. A goal directed backward form of reasoning was employed for evaluating the suitability of a site for a terrain related engineering application. The reasoning strategy was formalized in production rules, and the fuzzy models of terrain terms were formalized in frames. Procedural computations were formalized in LISP code. The methodology was implemented in the Terrain Analysis eXpert (TAX) system. TAX was developed by employing the expert system shell KEE (Knowledge Engineering Environment) and the image processing package ELAS (Earth resources Laboratory Application Software). TAX was tested with a real data set consisting of a digitized color infra-red photograph and digital elevation data. The conclusions arrived at by TAX compared favorably to those reached by an expert who analyzed the same site using traditional photointerpretation techniques.
机译:地形分析是对与原产地和独特地形单元(称为地形)组成有关的图像模式的系统研究。它考虑并提供了有关物理场地因素的信息,土木工程师使用这些信息来评估场地是否适合地形相关工程应用。地形分析是一项耗时的劳动密集型过程,需要大量专业知识。本文采用专家系统范式,开发了一种解决地形分析问题的计算方法。开发了一种用于表示和管理不确定地形知识的方法。使用模糊模型表示了地形分析术语描述中固有的“模糊性”。采用了Dempster-Shafer证据理论,根据观察到的证据建立了有关地形类型的假设。目标定向推理的后向形式用于评估站点是否适合地形相关工程应用。推理策略在生产规则中正式化,地形术语的模糊模型在框架中正式化。程序计算以LISP代码形式化。该方法已在Terrain Analysis eXpert(TAX)系统中实施。通过使用专家系统外壳KEE(知识工程环境)和图像处理软件包ELAS(地球资源实验室应用软件)来开发TAX。使用包含数字化彩色红外照片和数字高程数据的真实数据集对TAX进行了测试。 TAX得出的结论比起使用传统照片解释技术分析同一地点的专家得出的结论要好。

著录项

  • 作者

    Narasimhan, Ravi.;

  • 作者单位

    Louisiana State University and Agricultural & Mechanical College.;

  • 授予单位 Louisiana State University and Agricultural & Mechanical College.;
  • 学科 Engineering Civil.; Computer Science.; Artificial Intelligence.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 1990
  • 页码 269 p.
  • 总页数 269
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;自动化技术、计算机技术;人工智能理论;遥感技术;
  • 关键词

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