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1 
Interpretation and estimation of membership functions.January 1993 (has links)
by Chow Kan Shing. / Includes questionnaire in Chinese. / Thesis (M.Phil.)Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 100103). / Chapter Chapter 1.  Introduction  p.1 / Chapter Chapter 2.  A Brief Review on Fuzzy Set Theory  p.3 / Chapter 2.1.  The Concept of Fuzzy Set Theory  p.3 / Chapter 2.2.  Fundamental Operations on Fuzzy Sets  p.4 / Chapter 2.3.  Two Approaches to Investigate Fuzzy Set Theory  p.6 / Chapter Chapter 3.  The Interpretation of the Membership Function  p.7 / Chapter 3.1.  Review and Comparison of the Interpretation of the Membership Values  p.7 / Chapter 3.1.1.  Interpretation in terms of Betting / Chapter 3.1.2.  Interpretation in terms of Payoff Function / Chapter 3.1.3.  Interpretation in terms of Amount of Relevant Attribute / Chapter 3.1.4.  Interpretation in terms of the TEE Model / Chapter 3.1.5.  Interpretation in terms of a Measurement Model / Chapter 3.1.6.  Interpretation in terms of Prototype Theory / Chapter 3.2.  Discussion about Membership Function  p.29 / Chapter Chapter 4.  Estimation of the Membership Function  p.33 / Chapter 4.1.  The Data Collection Methods for the Estimation of the Membership Function  p.34 / Chapter 4.1.1.  Direct Rating / Chapter 4.1.2.  Polling / Chapter 4.1.3.  Setvalued Statistics / Chapter 4.1.4.  Reverse Rating / Chapter 4.2.  Estimation Procedures for the Membership Function and their Characteristics  p.36 / Chapter 4.2.1.  Nonparametric Estimation Procedures / Chapter 4.2.2.  The Characteristics of the Nonparametric Estimation Procedures / Chapter 4.2.3.  Parametric Estimation Procedures / Chapter 4.3.  Connections between the Four Data Collection Methods  p.58 / Chapter 4.3.1.  Connection between Direct Rating and Polling / Chapter 4.3.2.  Connection between Polling and Reverse Rating / Chapter 4.3.3.  Connection between Reverse Rating and Setvalued Statistics / Chapter 4.4.  Other Estimation Procedures  p.71 / Chapter 4.4.1.  Procedure based on Saaty's Matrix / Chapter 4.4.2.  Procedure based on Mabuchi's Interpretation of the Membership Function / Chapter 4.5.  The Survey  p.77 / Chapter 4.5.1.  Introduction of the Survey / Chapter 4.5.2.  The Result of the Survey / Chapter 4.5.3.  An Approach to reduce the 'bias' in Polling / Chapter 4.5.4.  Advice to Researchers / Chapter Chapter 5.  Discussion  p.97 / References  p.100 / Appendix: Questionnaire

2 
Interlocking difference sets /Fan, Chuntak. January 1986 (has links)
ThesisM. Phil., University of Hong Kong, 1986.

3 
Interlocking difference sets范俊德, Fan, Chuntak. January 1986 (has links)
published_or_final_version / Mathematics / Master / Master of Philosophy

4 
The wellordering of setsPerkins, Harold Everett January 1959 (has links)
Thesis (M.A.)Boston University

5 
Expert fuzzy control based upon manintheloop model identificationShaw, Ian Stephan 11 June 2014 (has links)
M.Ing. (Electrical & Electronic Engineering) / A dynamic process is considered modelled and identified when the model can predict its future behaviour as a result of a known stimulus. However, practical reality is complex and it is quite difficult to totally encompass a model representing a physical phenomenon in a mathematical formulation. Besides, to keep such formulations tractable, certain restrictive assumptions such as, for example, linearity, are often required. The common feature of general controltheoretic methods used for modelling is that they presuppose the valid and accurate knowledge of the processes to be controlled. If, however, one does not understand the inner workings of a complex process that one wishes to model, traditional techniques rarely yield satisfactory results. As systems become more complex it becomes increasingly difficult to make mathematical statements about them which are both meaningful and precise. Thus one is compelled to concede that imprecision and inexactness must be accepted in any real system application. The theory of fuzzy sets is a methodology for the handling of qualitative, inexact, imprecise, information in a systematic and rigorous way. This approach provides an excellent tool for the modelling of humancentered systems, especially because fuzziness seems to be an important facet of the human thinking process. Instead of using a precisely defined or measured value of a variable, a human being tends to summarize available information by classifying into vague and imprecise categories such as, for example, low, medium, high. In this way, the information received from the outside world is reduced to just what is needed to perform the task on hand with the required precision. Thus there is no need for precise mathematical models and thereby the human (i.e. fuzzy) decisionmaking mechanism has considerably less computational overhead and is thus faster and more conducive to biological survival than an equivalent precise mathematical model...

6 
On Projections of Nonseparable Souslin and Borel Sets Along SeparablePetr Holicky, Vaclav Kominek, Andreas.Cap@esi.ac.at 23 April 2001 (has links)
No description available.

7 
Methodology for the conceptual design of a robust and opportunistic systemofsystemsTalley, Diana Noonan. January 2008 (has links)
Thesis (Ph.D)Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Mavris, Dimitri; Committee Member: Bishop, Carlee; Committee Member: Brown, David; Committee Member: Costello, Mark; Committee Member: Schrage, Daniel. Part of the SMARTech Electronic Thesis and Dissertation Collection.

8 
A lemma on limits of analytic setsRosas, Rudy 25 September 2017 (has links)
This paper is a small remark on the analyticity of a limit of analytic sets in a particular case: when the sets are complex discs.

9 
Properties of Order Relations and Certain Partly Ordered SystemsBarros, David Nicholas 06 1900 (has links)
The purpose of this paper is to present a study of partly ordered sets. It includes a rigorous development of relations based on the notion of a relation as a set, lattices, and theorems concerning the lattice of subgroups of a group.

10 
Automated prototype inductionGonzaÌlez RodriÌguez, IneÌs January 2002 (has links)
No description available.

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