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Beginning ?rDwYG(u]@
1. In this paper, we focus on the need for "lZ<bG
2. This paper proceeds as follow. hH/O2
3. The structure of the paper is as follows. C=cTj7Ub
4. In this paper, we shall first briefly introduce fuzzy sets and related 9="sx 8?
concepts "!?bC#d#(
5. To begin with we will provide a brief background on the XEEbmIO*<9
Introduction -`UlntEdZ:
1. This will be followed by a description of the fuzzy nature of the 6f!mk:\T.
problem and a detailed presentation of how the required L /> GYx
membership functions are defined. O :^[4$~
2. Details on xx and xx are discussed in later sections. qI^jwl|k
3. In the next section, after a statement of the basic problem, various $ZO<8|bW
situations involving possibility knowledge are investigated: first, an ]Dg0@Y
entirely possibility model is proposed; then the cases of a fuzzy B_2>Yt"
service time with stochastic arrivals and non-fuzzy service rule is du,-]fF
studied; lastly, fuzzy service rule are considered. w#,v n8
Review :nUsC+oBS
1. This review is followed by an introduction. \[EWxu
2. A brief summary of some of the relevant concepts in xxx and xxx is O$/swwB!
presented in Section 2. G{~p.?f:
3. In the next section, a brief review of the .... is given. z]AS@}wWqg
4. In the next section, a short review of ... is given with special regard %ko 8P
to ... 8v
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5. Section 2 reviews relevant research related to xx. EIQy?ig
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6. Section 1.1 briefly surveys the motivation for a methodology of dRa<,@1"
action, while 1.2 looks at the difficulties posed by the complexity of m4>oE|\
systems and outlines the need for development of possibility &X,)+b=
methods. ueBoSZRWX
Body K<JP9t6Qd
1. Section 1 defines the notion of robustness, and argues for its @I6 A9do
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importance. Bqlc+d:
2. Section 1 devoted to the basic aspects of the FLC decision-making .@-]A
logic. [+,U0OV,
3. Section 2 gives the background of the problem which includes xxx G3^]Wwu
4. Section 2 discusses some problems with and approaches to, 1/+r?F3
natural language understanding. kGV`Q
5. Section 2 explains how flexibility which often ... can be expressed uN3J)@;_
in terms of fuzzy time-window ,ri--<
6. Section 3 discusses the aspects of fuzzy set theory that are used in XPo'iI-
the ... [<a%\:c m4
7. Section 3 describes the system itself in a general way, including >/kG5]zxY
the ….. and also discusses how to evaluate system performance. @SG"t,5s
8. Section 3 describes a new measure of xx. S&]<;N_B
9. Section 3 demonstrates the use of fuzzy possibility theory in the DB'KIw
analysis of xx. 6ilC
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10. Section 3 is a fine description of fuzzy formulation of human /1#Q=T
decision. '=G
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11. Section 3 is developed to the modeling and processing of fuzzy 8yz((?LrDh
decision rules '!h0![OH
12. The main idea of the FLC is described in Section 3 while Section 4 02#Iip3t
describes the xx strategies.
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13. Section 3 and 4 show experimental studies for verifying the `$agM@"^
proposed model. o]jP3
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14. Section 4 discusses a previous fuzzy set-based approach to cost (My$@l973
variance investigation. ~G:2iSi(#
15. Section 4 gives a specific example of xxx. *[~o~e/YCb
16. Section 4 is the experimental study to make a fuzzy model of }%FuL5Tx
memory process. 1
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17. Section 4 contains a discussion of the implication of the results of ~TFYlV
Section 2 and 3. {!e ANm'
18. Section 4 applies this fuzzy measure to the analysis of xx and KPd C9H
illustrate its use on experimental data. l(w vQO
19. Section 5 presents the primary results of the paper: a fuzzy set OC>_=i$'
model .. qM!f
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20. Section 5 contains some conclusions plus some ideas for further .0fh>kQ
work. /b:t;0G
21. Section 6 illustrates the model with an example. ^0tf1pV2
22. Various ways of justification and the reasons for their choice are 1H,tP|s
discussed very briefly in Section 2. oTD-+MZn
23. In Section 2 are presented the block diagram expression of a 71/ m.w
whole model w Al}:|+n
of human DM system cI%"Ynq"3
24. In Section 2 we shall list a collection of basic assumptions which 9kX=99kf[
a ... scheme must satisfy. H1%[\X?=
25. In Section 2 of this paper, we present representation and ?X#/1X%u:
uniqueness theorems for the fundamental measurement of fuzziness #;"D)C
when the domain of discourse is order-dense. w0j/\XN2s
26. In Section 3, we describe the preliminary results of an empirical *fH_lG%
study ,c%K)KuPK.
currently in progress to verify the measurement model and to I' ! r
construct membership functions. ]C
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27. In Section 5 is analyzed the inference process through the two 3 IWLBc
kinds of inference experiments... )o9Q5Lq
This Section v"~Do+*+
1. In this section, the characteristics and environment under which M6jp1:ZH2q
MRP is designed are described. h^A3 0f_x
2. We will provide in this section basic terminologies and notations ) Kc%8hBv
which are necessary for the understanding of subsequent results. MZ5Y\-nq\
Next Section S~k*r{?H})
2. The next section describes the mathematics that goes into the sp=OT-Pfp
computer implementation of such fuzzy logic statements. 1@%B?
3. However, it is cumbersome for this purpose and in practical N~):c2Kp<9
applications the formulae were rearranged and simplified as *!g 24
discussed in the next section. x*h?%egB!p
4. The three components will be described in the next two section, 3duG.iUlL
and an example of xx analysis of a computer information system will `k(u:yGK
@n7t?9Bx
then illustrate their use. ]am~aJ|L
5. We can interpret the results of Experiments I and II as in the a#+>w5
following sections.
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6. The next section summarizes the method in a from that is useful J ;
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for arguments based on xx Q PFeBl
Summary s) Cpi
1. This paper concludes with a discussion of future research Mlv<r=E
consideration in section 5. I?a8h`WS+
2. Section 5 summarizes the results of this investigation. co5y"yj_
3. Section 5 gives the conclusions and future directions of research. F#(.v7
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4. Section 7 provides a summary and a discussion of some extensions _i3i HR?
of the paper. l80bHp=
5. Finally, conclusions and future work are summarized V43nws"4
6. The basic questions posed above are then discussed and E'5Ajtw;
conclusions are drawn. 'nRp}s1^[
7. Section 7 is the conclusion of the paper.
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Chapter 0. Abstract cYGRy,'gH
1. A basic problem in the design of xx is presented by the choice of a ?75\>NiR
xx rate for the measurement of experimental variables. )ll?-FZ
2. This paper examines a new measure of xx in xx based on fuzzy q0&Wk"X%rr
mathematics which overcomes the difficulties found in other xx ht?CHUu
measures. ||uZ bP@
3. This paper describes a system for the analysis of the xx. _N98 vf0o
4. The method involves the construction of xx from fuzzy relations. VS?dvZ1cC
5. The procedure is useful in analyzing how groups reach a decision. vXephR'
6. The technique used is to employ a newly developed and versatile Fse['O
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xx algorithm. ,Ij=b
7. The usefulness of xx is also considered. Dy su{rL
8. A brief methodology used in xx is discussed. 2s 7mI'
9. The analysis is useful in xx and xx problem. M
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10. A model is developed for a xx analysis using fuzzy matrices. J' W}7r
11. Algorithms to combine these estimates and produce a xx are E*BSfn&i
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presented and justified. h1#S+k
12. The use of the method is discussed and an example is given. Y)|~:& tZ
13. Results of an experimental applications of this xx analysis <"?*zx&