L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3-28 (1978). Home/Search Document Not in Database Summary Related Articles Check |
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Stability in Possibilistic Quadratic Programming - Canestrelli, Giove.. (Correct)
....principle in the usual way. Let andB be fuzzy numbers and [ a 1 (#) a 2 (#) B ] b 1 (#) b 2 (#) for all # [0, 1] We metricize the set of fuzzy numbers by the metric [9] d( sup ##[0,1] max a 1 (#) b 1 (#) a 2 (#) b 2 (#) According to Zadeh s possiblity theory [12] we hav e Poss[B ] sup x#y min (x) B (y) sup ) t) 2) where stands for , #, or . We will need the following lemmas [7] Lemma 1 Let ,B , C and D be fuzzy numbers and let t IR . Then t,B t) t d( B ) d( C,B D) d(C,D) Lemma 2 Let x 1 , x 2 be real numbers such ....
L.A.Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1(1978) 3-28.
Fuzzy Control and Coherent Functions - Chemello And Sossai (Correct)
....event or property. Such an error can be seen as the complement of a similarity degree between an ideal or prototypical percept and the actual observation. Similarity degrees are assumed as an intended semantics for possibility theory [2, 3] Possibility theory has been introduced by L.A. Zadeh [4] to represent the imprecision that is intrinsic in natural language . This imprecision, called by some authors linguistic uncertainty to stress the di#erence with respect to stochastic uncertainty, described by probability theory, is represented by possibility distributions. We will use two ....
L. A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3--28, 1978.
Coherent Functions in Autonomous Systems - Sossai, Chemello (2002) (Correct)
....event or property; such an error can be seen as the complement of a similarity degree between an ideal or prototypical percept and the actual observation. Similarity degrees are assumed as an intended semantics for possibility theory [12, 29] Possibility theory has been introduced by L.A. Zadeh [36] to represent the imprecision that is intrinsic in natural language. This imprecision, called by some authors linguistic uncertainty to stress the difference with respect to stochastic uncertainty, described by probability theory, is represented by possibility distributions, i.e. fuzzy sets. ....
Zadeh, L. A. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3-28.
Some Normative Properties of Possibility Distributions - Carlsson, Fullér.. (Correct)
.... # (the closure of the support of A)if# =0.IfA #Fis a fuzzy number then [A] is a convex and compact subset of for all # [0, 1] Fuzzy numbers can be considered as possibility distributions. Let a, b #,# b, then the possibility that A #Ftakes its value from [a, b] is defined by [7] Po#2 A [a, b] max x#[a,b] A(x) A fuzzy set B in is said to be a joint possibility distribution of fuzzy numbers A i i =1, m, if it satisfies the relationship x j #R,j #=i B(x 1 , x m) A i (x i ) i R,i=1, m. Furthermore, A i is called the i th marginal possibility ....
L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1(1978) 3-28.
A Review of Uncertainty Handling Formalisms - Parsons, Hunter (1998) (5 citations) (Correct)
.... Shafer reformulated the theory and published it as A Mathematical Theory of Evidence in 1976 [82] This body of work, often referred to as Dempster Shafer theory, has several interpretations including the transferable belief model [87, 90] Another much studied approach is possibility theory [26, 103] which grew out of work on fuzzy sets [102] There are numerous other numerical techniques for dealing with uncertainty often developed from pragmatic considerations. These include certainty factors [86] probabilistic logic [63] and belief intervals [21] to name but a few. The methods that we ....
.... belief is assigned is a contentious issue, though all the theories that we shall consider assume allocation by an assignment function that distributes belief to possible events under consideration. Belief may be distributed on the basis of statistical information [81, 92] physical possibility [103], or purely subjective assessment [12] by an expert or otherwise. The belief assigned is a number between 0 and 1, with 0 being the belief assigned to a fact that is known to be false, and 1 the belief assigned to a fact known to be definitely true. The infinite number of degrees of belief between ....
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L. A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:1--28, 1978.
Yoda, an Adaptive Oft Classification Model: Content-based.. - Chen, Shahabi (2003) (Correct)
....precise values is almost impossible. Moreover, different people have different interpretations of words. That is, the information describing personalities, physical features, preferences and personal evaluation is imprecise. To handle this uncertainty during the query processes, fuzzy logic (FL) [22] is adopted by our system. The concept of FL was first introduced by Zadeh [22] to problems for which precise formulation is not possible. The original FL has the weakness that uncertainty cannot be considered during the computation. Therefore, Karnik and Mendel [23,24] advocated type 2 FLto ....
....interpretations of words. That is, the information describing personalities, physical features, preferences and personal evaluation is imprecise. To handle this uncertainty during the query processes, fuzzy logic (FL) 22] is adopted by our system. The concept of FL was first introduced by Zadeh [22] to problems for which precise formulation is not possible. The original FL has the weakness that uncertainty cannot be considered during the computation. Therefore, Karnik and Mendel [23,24] advocated type 2 FLto overcome this disadvantage. However, for the sake of simplicity, we only consider ....
Zadeh L (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 1(1):3--28
Mining Association Rules with Uncertain Item.. - Shyu, Haruechaiyasak.. (Correct)
....process more generalized. To deal with the above uncertainty in the data sets, the Dempster Shafer (DS) evidential reasoning theory [6] 13] is applied in the association rule mining process. Unlike some other approaches in handling uncertainty in data sets such as fuzzy set and possibility theory [18], evidence theory allows us to model and construct the it emsets easily via its basic probability assignment (bpa) or mass function (m) Using the bpa, the item interrelationships and multiplicity can be conveniently captured within the framework [10] as shown in the next section. We propose the ....
L. A. Zadeh, "Fuzzy Sets as a Basis for a Theory of Possibility," Fuzzy Sets System, vol. 1, no. 1, pp. 328, 1978.
Possibility Distributions: A Normative View - Carlsson, Fullér.. (Correct)
....(the closure of the support of A)if# =0.If A #Fis a fuzzy number then [A] is a convex and compact subset of for all # [0, 1] Fuzzy numbers can be considered as possibility distributions. Let a, b #,# b, then the possibility that A #Ftakes its value from [a, b] is definedby[7]Po s(A [a, b] max x#[a,b] A(x) A fuzzy set B in is said to be a joint possibility distribution of fuzzy numbers A i i =1, m,ifitsatisfies the relationship x j #R,j #=i B(x 1 , x m) A i (x i ) i R,i=1, m. Furthermore, A i is called the i th marginal possibility ....
L. A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, 1(1978) 3-28.
A Context-Dependent Method for Ordering Fuzzy.. - Yager, Detyniecki, .. (2001) (Correct)
....all the fuzzy numbers being ordered are measured. 2. Comparing fuzzy numbers using a probability distribution When expressing the value of a variable V, such as the beginning time of an event or the payoff associated with a decision, as a fuzzy subset we are inducing a possibility distribution [8] over the domain of the variable. In particular, the statement V is F, where F is a fuzzy set, can be seen as inducing a possibility distribution H on the domain of V such that for each x, F(x) II(x) From the initial introduction of the idea of possibility, starting with Zadeh s possibility ....
.... In particular, the statement V is F, where F is a fuzzy set, can be seen as inducing a possibility distribution H on the domain of V such that for each x, F(x) II(x) From the initial introduction of the idea of possibility, starting with Zadeh s possibility probability consistency principle , [8] considerable interest has focused on the relationship between possibility and probability. A number of researchers have looked at the problem of associating probability distributions with possibility distributions and have suggested methods of conversion [9] All of these share the fundamental ....
L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems 1 (1978) 38. 255
A Comparison of Decision-Level Sensor-Fusion.. - Cremer, Schutte.. (2001) (1 citation) (Correct)
....challenge may be tackled by assuming certain properties of the conditional probabilities. 2.2. Non statistical fusion techniques Besides the statistical approach, other techniques for decision level fusion exist. Common techniques include applications of Dempster Shafer theory [35] fuzzy logic [36], rule based fusion [37] and voting techniques [38] Although these techniques are not statistical, they can be described with discriminant functions in sensor confidence space with corresponding error functions. This notion allows us to compare different fusion methods on the capability of the ....
L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy sets and systems 1 (1978) 3 28.
Sensor Data Fusion for Anti-Personnel Land-Mine - Cremer, den Breejen, Schutte (1998) (Correct)
....equal to the uncertainty is used. 2.4 Fuzzy rules The membership function of fuzzy sets can be interpreted as a possibility distribution. This differs from a probability distribution in the sense that it does not indicate the relative number of occurrences within a given measurement, see also [3]. There are two ways of combining possibilities: using the and or or relationship, which are defined as the minimum and the maximum operator respectively. For detection of mines, a set of rules is derived, with each rule combined using the or relation. Each rule consists of the and ....
L.A. Zadeh, "Fuzzy sets as a basis for the theory of possibility" in "Fuzzy Sets and Systems", Volume 1, North-Holland Publishing Company, 1978
Using Probability Trees to Compute Marginals with Imprecise.. - Cano, Moral (2000) (2 citations) (Correct)
....[3, 22] This work has been supported by CICYT under project TIC97 1135 C04 01. ffl To model conflict between several sources of information [52, 36] There is a variety of mathematical models for imprecise probability [53, 57] comparative probability orderings [25, 26] possibility measures [60, 23], fuzzy measures [48, 58, 28] belief functions [43, 47] Choquet capacities [29, 14] interval probabilities [59, 18] convex sets of probabilities [13, 53, 19] Among all these models we think that convex sets of probabilities is the most appropriate to represent and calculate with imprecise ....
L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3--28, 1978.
Cerberus: A Context-Aware Security Scheme for Smart.. - Al-Muhtadi.. (Correct)
....more flexible by utilizing confidence information. Several reasoning techniques can be used to combine confidence values and calculate a net confidence value for a particular principal. The techniques we have considered so far include simple probabilities, Bayesian probability, and fuzzy logic [6]. In Section 5, we give more details on how we use confidence values in access control decisions. Since identification and authentication can use a large number of diverse devices and as technology improves and new authentication devices become available, security systems need a dynamic method ....
L. Zadeh, "Fuzzy sets as basis for a theory of possibility," Fuzzy Sets and Systems, vol. 1, pp. 3-28, 1978.
Visual Models for Real-Time Embedded Systems - Chantrapornchai, Sunetnanta (2001) (Correct)
....definition is given in a form of processes and their process execution flow. Then, in details of how the process is implemented, the activity model is used. At each level of the design view, timing property is defined as an object composing of many characteristics. A triangular fuzzy number [11] can be used to represent timing value. Rather than a single value, it supports the case for varying timing values. The timing object is inherited from the upper structure level down to activity level while preserving consistency of defining timing values among these levels. Models In this ....
L. A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3-28, 1978.
Unknown - Information Systems Vol (Correct)
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L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3-28 (1978).
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Zadeh L., Fuzzy Sets as a Basis for a Theory of Possibility, Fuzzy Sets and Systems 1, pp.3-28, 1978 .
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L. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 1(1):3-28, 1978.
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L. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 1(1):3-28, 1978.
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Zadeh L (1978) Fuzzy Sets as a Basis for a Theory of Possibility. Fuzzy Sets and Systems 1:3-28
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L. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 1(1):3-28, 1978.
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L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1:3--28, 1978.
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L.A. Zadeh. Fuzzy Sets as a Basis for a Theory of Possibility. Fuzzy Sets and Systems, 1:3-28, 1978.
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L. A. Zadeh, Fuzzy sets as a basis for theory of possibility, Fuzzy Sets and Systems, 1 (1978), pp. 3--28. Ji rina Vejnarov a is with the Laboratory for Intelligent Systems of the University of Economics, Prague, Czech Republic. She is also a senior research fellow of the Institute for Information Theory and Automation of the Academy of Sciences of the Czech Republic. E-mail: vejnar@vse.cz
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