Thesis (Ph. D.)--University of Hong Kong, 1991.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 141-147). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Washington, 1996. / Vita. Includes bibliographical references (leaves [74]-78).

Thesis (M.S. in Computer Science) Naval Postgraduate School, September 1996. / Thesis advisor(s): Robert McGhee and Don Brutzman. "September 1996." Appendix videotape located at Circulation Desk, call number VHS 5000067. Includes bibliographical references (p. 179-184). Also available online.

Thesis (Ph. D.)--University of Maryland, 1990. / Includes bibliographical references (leaves 400-407).

Thesis (Ph.D.)--Aberdeen University, 2009. / Title from web page (viewed on June 26, 2009). Includes bibliographical references.

Thesis (M.S. in Systems Engineering)--Naval Postgraduate School, December 2005. / Thesis Advisor(s): John Osmundson. Includes bibliographical references (p. 81-84). Also available online.

Recent advances in geographic information systems (GIS) and artificial intelligence (AI) techniques have been summarised, concentrating on the theoretical aspects of their construction and use. Existing projects combining AI and GIS have also been discussed, with attention paid to the interfacing methods used and problems uncovered by the approaches. AI and GIS have been combined in this research to create an intelligent GIS for design. This has been applied to off-shore pipeline route design. The system was tested using data from a real pipeline design project.

No description available.

The work described in this thesis stems from the idea that expert systems should be able to accurately and appropriately handle uncertain information. The traditional approaches to dealing with uncertainty are discussed and are shown to contain many inadequacies. The Dempster-Shafer, or D-S, theory of evidence is proposed as an appealing theoretical basis for representing uncertain knowledge and for performing inexact reasoning in expert systems. The D-S theory is reviewed in some detail; including its approaches to representing concepts, to representing belief, to combining belief and to performing inference. The D-S implementation approaches pursued by other researchers are described and critiqued. Attempts made early in the thesis research which failed to achieve the important goal of consistency with the D-S theory are also reviewed. Two approaches to implementing D-S theory in a completely consistent manner are discussed in detail. It is shown that the second of these systems, a frame network approach, has led to the development of a fully functional prototype expert system shell called FRO. In this system, concepts are represented using D-S frames of discernment, belief is represented using D-S belief functions, and inference is performed using stored relationships between frames of discernment (forming the frame network) and D-S belief combination rules. System control is accomplished using a discrete rule-based control component and uncertain input and output are performed through an interactive belief interface system called IBIS. Each of these features is reviewed. Finally, a simple but detailed example of an application of a frame network expert system is provided. The FRO system user's documentation is provided in the appendix. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate