bluuebunny/crossref_metadata_2025 huggingface dataset:
ABSORBING LAYER VIA WAVE-EQUATION SPLITTING
Authors: CARCIONE JOSÉ M. , CAVALLINI FABIO
Published: April 2003

Modeling acoustic waves generated by a localized source is always vexed by the nagging problem of spurious reflections and wraparound arising when the wavefront reaches the boundary of the numerical mesh. This difficulty may be circumvented by using a very large computational domain, which is very inefficient, or can be tackled by using some kind of absorbing boundary technique, which has not yet found a universally satisfactory solution. In this work, the wave equation is modified by introducing a term that is nonzero only in a narrow strip near the boundary. Then, a splitting technique permits to compute part of the solution analytically (hence, at no computational cost), while an application of Weyl's formula for the exponential of a matrix leads to a second-order accurate scheme that completes the algorithm. An application to SH seismic wave modeling shows that the performance of the present method is competitive with standard ones. Moreover, there is evidence for a potential application to the modeling of wave propagation in porous media, where stiff differential equations arise.
JOINT 3D TRAVELTIME INVERSION OF P, S AND CONVERTED WAVES
Authors: ROSSI GIULIANA , VESNAVER ALDO
Published: April 2003

Converted waves can play a basic role in the traveltime inversion of seismic waves. The sought velocity fields of P and S waves are almost decoupled, when considering pure P and S arrivals: their only connection are the possible common reflecting interfaces in the Earth. Converted waves provide new equations in the linear system to be inverted, which directly relates the two velocity fields. Since the new equations do not introduce additional unknowns, they increase the system rank or its redundancy, so making its solutions better constrained and robust.
MODIFICATIONS OF THE GROUND MOTION IN DENSE URBAN AREAS
Authors: CLOUTEAU DIDIER , AUBRY DENIS
Published: April 2003

The main motivation of this work is to analyze whether or not the presence of buildings is able to modify the seismic field significantly. We first present a numerical method able to account for a three-dimensional building distribution resting on a layered elastic-half-space. The proposed method is based on a variational coupling between Boundary Elements and modal representation for the buildings. Provided with the hypothesis of a stochastic homogeneous distribution of these buildings or a deterministic periodic one, a realistic model of an entire city may be accounted for. This method is applied to practical situations and it is shown that modifications of the incident field occur mainly for soft layered soils. However from an engineering point of view, it appears that the amplification levels are not significantly modified even in these extreme cases. Nevertheless, a strong scattering of the response inside the city depends on the nearby buildings can be observed.
AILU FOR HELMHOLTZ PROBLEMS: A NEW PRECONDITIONER BASED ON THE ANALYTIC PARABOLIC FACTORIZATION
Authors: GANDER MARTIN J. , NATAF FRÉDÉRIC
Published: April 2003

We investigate a new type of preconditioner which is based on the analytic factorization of the operator into two parabolic factors. Approximate analytic factorizations lead to new block ILU preconditioners. We analyze the preconditioner at the continuous level where it is possible to optimize its performance. Numerical experiments illustrate the effectiveness of the new approach.
EARTHQUAKE GROUND MOTION SIMULATION THROUGH THE 2-D SPECTRAL ELEMENT METHOD
Authors: PRIOLO ENRICO
Published: April 2003

The application of the 2-D Chebyshev spectral element method (SPEM) to engineering seismology problems is reviewed in this paper. The SPEM is a high-order finite element technique which solves the variational formulation of the seismic wave propagation equations. The computational domain is discretised into an unstructured grid composed by irregular quadrilateral elements. This property makes the SPEM particularly suitable to compute numerically accurate solutions of the full wave equations in complex media. The earthquake is simulated following an approach that can be considered "global", that is all the factors influencing the wave propagation — source, crustal heterogeneity, fine details of the near-surface structure, and topography — are taken into account and solved simultaneously. The basic earthquake source is represented by a 2-D point double couple model. Ruptures propagating along fault segments placed on the model plane are simulated as a finite summation of elementary point sources. After a general introduction, the paper first gives an overview of the method; then it concentrates on some methodological topics of interest for practical applications, such as quadrangular mesh generation, source definition and scaling, numerical accuracy and computational efficiency. Limitations and advantages of using a 2-D approach, although sophisticated such as the SPEM, are addressed, as well. The effectiveness of the method is illustrated through two case histories, i.e. the ground shaking prediction in Catania (Sicily, Italy) for a catastrophic earthquake, and the analysis of the ground motion in the presence of a massive structure.
SOME GROUP THEORETIC ASPECTS OF t-NORMS
Authors: RICHMAN FRED , WALKER ELBERT
Published: April 2003

Let A be the automorphism group of the unit interval with its usual order relation, and let ℝ+ be the embedding of the multiplicative group of positive real numbers into A given by exponentiation. Strict t-norms are in one-to-one correspondence with the right cosets of ℝ+ in A. Here, we identify the normalizer of ℝ+ in A and give explicit formulas for the corresponding set of t-norms.
ON MODUS PONENS GENERATING FUNCTIONS
Authors: PRADERA ANA , TRILLAS ENRIC , CUBILLO SUSANA
Published: April 2003

This paper investigates the use of functions other than t-norms to model the Modus Ponens rule in a fuzzy inference process. For that purpose, new definitions for fuzzy inference related concepts are suggested, that take into account the possibility of using a larger class of functions. In particular, the concept of "Modus Ponens generating function" is revisited, allowing to find out when and where (in which subset of the defined universe) an operator is able to generate the Modus Ponens scheme. In addition, given such an operator, the conditional relations that may be used along with it to model an inference process are found. These results are applied to some common operators, finding their Modus Ponens generation capacity as well as their corresponding residuated fuzzy conditionals. Finally, the relation between an operator's ability to describe the Modus Ponens rule and its conjunctive/disjunctive behaviour is also studied, by means of a series of sufficient and/or necessary conditions relating both concepts.
A NEW APPROACH TO LEARNING LINGUISTIC CONTROL RULES
Authors: BALDWIN J. F. , LAWRY J.
Published: April 2003

The mass assignment ID3 (MA-ID3) algorithm for generating linguistic decision trees is introduced together with the mass assignment semantics for linguistic variables. The potential of this algorithm for learning control rules is illustrated by means of the Van de Pol system. A data set of control paths is generated using an existing on-line controller. This is then used to generate a set of quantified linguistic control rules. The effectiveness and robustness of this rule-base is then demonstrated.
ADVANCES IN MEDIA THEORY
Authors: OVCHINNIKOV SERGEI , DUKHOVNY ALEXANDER
Published: April 2003

Media theory is a new branch of mathematical social and behavioral sciences with applications ranging from combinatorics to political sciences. Because of the generality of the concept of a medium and the natural character of its defining axioms, we believe the theory has a potential to become a new methodology for the management of imprecise, uncertain or incomplete information.

In this paper, we review the basic concepts of media theory and present some advances in its combinatorial and stochastic parts. We prove that any medium is isomorphic to a submedium of a complete oriented medium and characterize these submedia. We also present some results concerning the stochastic evolution of a complete oriented medium and some of its submedia.
ON A THEOREM PROVER FOR VARIATIONAL LOGIC PROGRAMS WITH FUNCTORS SETU AND SETS
Authors: SAKAI HIROSHI , OKUMA AKIMICHI
Published: April 2003

We are now touching a problem how we add soft computing aspects to logic programming and we have been discussing null attribute values on logic programs. Here, we introduce two functors setu and sets into logic programs for describing indefinite attribute values explicitly. Every logic program with setu or sets has variability and tolerance in itself, namely this program expresses a set of possible definite logic programs. We call this program a variational logic program. In this paper, we show the variational logic programs and a theorem prover for them.
AN OVERVIEW OF ROUGH SET SEMANTICS FOR MODAL AND QUANTIFIER LOGICS
Authors: LIAU CHURN-JUNG
Published: April 2003

In this paper, we would like to present some logics with semantics based on rough set theory and related notions. These logics are mainly divided into two classes. One is the class of modal logics and the other is that of quantifier logics. For the former, the approximation space is based on a set of possible worlds, whereas in the latter, we consider the set of variable assignments as the universe of approximation. In addition to surveying some well-known results about the links between logics and rough set notions, we also develop some new applied logics inspired by rough set theory.
INTERVAL METHODS IN KNOWLEDGE REPRESENTATION
Authors: KREINOVICH VLADIK
Published: April 2003

This section is maintained by Vladik Kreinovich. Please send your abstract (or copies of papers that you want to see reviewed here), to vladik@cs.utep.edu, or by regular mail to: Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA.
COHERENCE OF DEMPSTER'S CONDITIONING RULE IN DISCRETE POSSIBILISTIC MARKOV MODELS
Authors: JANSSEN HUGO J. , DE COOMAN GERT , KERRE ETIENNE E.
Published: April 2003

We consider discrete possibilistic systems for which the available information is given by one-step transition possibilities and initial possibilities. These systems can be represented, or modelled, by a collection of variables satisfying a possibilistic counterpart of the Markov condition. This means that, given the values assumed by a selection of variables, the possibility that a subsequent variable assumes some value only depends on the value taken by the most recent variable of the selection. The one-step transition possibilities are recovered by computing the conditional possibility of any two consecutive variables. Under the behavioural interpretation as marginal betting rates against events these 'conditional' possibilities and the initial possibilities should satisfy the rationality criteria of 'avoiding sure loss' and 'coherence'. We show that this is indeed the case when the conditional possibilities are defined using Dempster's conditioning rule.
DEMPSTER BELIEF FUNCTIONS ARE BASED ON THE PRINCIPLE OF COMPLETE IGNORANCE
Authors: WAKKER PETER P.
Published: April 2003

This paper shows that a "principle of complete ignorance" plays a central role in decisions based on Dempster belief functions. Such belief functions occur when, in a first stage, a random message is received and then, in a second stage, a true state of nature obtains. The uncertainty about the random message in the first stage is assumed to be probabilized, in agreement with the Bayesian principles. For the uncertainty in the second stage no probabilities are given. The Bayesian and belief function approaches part ways in the processing of the uncertainty in the second stage. The Bayesian approach requires that this uncertainty also be probabilized, which may require a resort to subjective information. Belief functions follow the principle of complete ignorance in the second stage, which permits strict adherence to objective inputs.
OPEN-FRAME DEMPSTER CONDITIONING FOR INCOMPLETE INTERVAL PROBABILITIES
Authors: CASTELLAN PAOLA , SGARRO ANDREA
Published: April 2003

In [2] a theory of incomplete interval probabilities has been put forward, which is meant to give a common framework to both interval probabilities and open-frame bodies of evidence, as obtained by application of the non-normalized Dempster rule. Below, as a continuation of [2], we compare two possible ways of "conditioning" based on a special case of the rule, i.e. open-frame Dempster conditioning.
APPLICATIONS OF POSSIBILITY AND EVIDENCE THEORY IN CIVIL ENGINEERING
Authors: FETZ THOMAS , OBERGUGGENBERGER MICHAEL , PITTSCHMANN SIMON
Published: April 2003

This article is devoted to applications of fuzzy set theory, possibility theory and evidence theory in civil engineering, presenting current work of a group or researchers at the University of Innsbruck. We argue that these methods are well suited for analyzing and processing the parameter uncertainties arising in soil mechanics and construction management. We address two specific applications here: finite element computations in foundation engineering and a queueing model in earth work.
PARTIAL PROBABILITY: THEORY AND APPLICATIONS
Authors: VOORBRAAK FRANS
Published: April 2003

In this paper, we describe an approach to handling partially specified probabilistic information. We propose a formalism, called Partial Probability Theory (PPT), which allows very general representations of belief states, and we give brief treatments of problems, like belief change, evidence combination, and decision making in the context of PPT. We argue that the generality of PPT provide new insights in all the mentioned problem areas. More detailed treatments of these issues can be found in several papers referred to in the text.
HOW SETS OF COHERENT PROBABILITIES MAY SERVE AS MODELS FOR DEGREES OF INCOHERENCE
Authors: SCHERVISH MARK J. , SEIDENFELD TEDDY , KADANE JOSEPH B.
Published: April 2003

We introduce two indices for the degree of incoherence in a set of lower and upper previsions: maximizing the rate of loss the incoherent bookmaker experiences in a Dutch Book, or maximizing the rate of profit the gambler achieves who makes Dutch Book against the incoherent bookmaker. We report how efficient bookmaking is achieved against these two indices in the case of incoherent previsions for events on a finite partition, and for incoherent previsions that include also a simple random variable. We relate the epsilon-contamination model to efficient bookmaking in the case of the rate of profit.
OPERATIONAL APPROACH TO GENERAL FUZZY MEASURES
Authors: RECHE FERNANDO , SALMERÓN ANTONIO
Published: April 2003

In this paper we propose an operational interpretation of general fuzzy measures. On the basis of this interpretation, we define the concept of coherence with respect to a partial information, and propose a rule of inference similar to the natural extension 7. We also suggest a definition of independence for fuzzy measures.
CHOQUET INTEGRAL MODELS AND INDEPENDENCE CONCEPTS IN MULTIATTRIBUTE UTILITY THEORY
Authors: MUROFUSHI T. , SUGENO M.
Published: April 2003

This paper discusses multiattribute preference relations compatible with a value/utility function represented by the Choquet integral with respect to a fuzzy measure, and shows that the additivity of the fuzzy measure is equivalent to each of mutual preferential independence, mutual weak difference independence, mutual difference independence, mutual utility independence, and additive independence.
GENERATION OF WEIGHTING TRIANGLES ASSOCIATED WITH AGGREGATION FUNCTIONS
Authors: CALVO T. , MAYOR G. , TORRENS J. , SUÑER J. , MAS M. , CARBONELL M.
Published: April 2003

In this work, we present several ways to obtain different types of weighting triangles, due to these types characterize some interesting properties of Extended Ordered Weighted Averaging operators, EOWA, and Extended Quasi-linear Weighted Mean, EQLWM, as well as of their reverse functions. We show that any quantifier determines an EOWA operator which is also an Extended Aggregation Function, EAF, i.e., the weighting triangle generated by a quantifier is always regular. Moreover, we present different results about generation of weighting triangles by means of sequences and fractal structures. Finally, we introduce a degree of orness of a weighting triangle associated with an EOWA operator. After that, we mention some results on each class of triangle, considering each one of these triangles as triangles associated with their corresponding EOWA operator, and we calculate the ornessof some interesting examples.
FUZZY BELIEF NETS
Authors: GOEBEL KAI F. , AGOGINO ALICE M.
Published: April 2003

This paper introduces fuzzy belief nets (FBN). The ability to invert arcs between nodes is key to solving belief nets. The inversion is accomplished by defining closeness measures which allow diagnostic reasoning from observed symptoms to cause of failures. The closeness measures are motivated by a Lukasiewicz operator which takes into account the distance from an observed symptom set to the modeled symptom set for all failure combinations. Hypothesized failures are then ranked according to maximum closeness measure and minimum cover, i.e., number of faults. Within the realm of fuzzy logic we show the graphical representation and solution of fuzzy belief nets.
FUZZY SETS AND FUZZY RELATIONAL STRUCTURES AS CHU SPACES
Authors: PAPADOPOULOS BASIL K. , SYROPOULOS APOSTOLOS
Published: April 2003

Chu spaces, which derive from the Chu construct of *-autonomous categories, can be used to represent most mathematical structures. Moreover, the logic of Chu spaces is linear logic. Most efforts to incorporate fuzzy set theory into the realm of linear logic are based on the assumption that fuzzy and linear negation are identical operations. We propose an incorporation based on the opposite assumption and we provide an interpretation of some linear connectives. Furthermore, we show that it is possible to represent any fuzzy relational structure as a Chu space by means of the functor G.
POINT MATCHING WITH A "SOFT" RELAXATION ALGORITHM
Authors: ROTBARD OREN , MITCHELL H. B. , ESTRAKH D. D.
Published: April 2003

Point-matching involves the matching of pairs of points from two sets of partially correlated points. It is an important task which is used in many different areas of signal processing. Although it is possible to perform point-matching using a brute-force algorithm, the high computational complexity makes it unfeasible even for a moderate number of points. In these circumstances an iterative relaxation algorithm is widely used. The traditional relaxation algorithm works well as long as the number of points in one set which do not have a corresponding pair in the second set is small and the positions of all the points are accurately known. When these conditions do not hold, the performance of the relaxation algorithm is substantially reduced. In this paper we formulate a "soft" relaxation algorithm using the concept of fuzzy linguistic quantifiers. The performance of the new relaxation algorithm is found to consistently exceed that of the traditional relaxation algorithm.
A HEDGE FOR GÖDEL FUZZY LOGIC
Authors: HÁJEK PETR , HARMANCOVÁ DAGMAR
Published: April 2003

We add to Gödel propositional fuzzy logic an unary connective originating in intuitionistic logic and having a natural meaning in fuzzy logic. We prove completeness with respect to a natural many-valued semantics.
COPING WITH UNCERTAINTY IN n-PERSON GAMES
Authors: GUIASU SILVIU
Published: April 2003

A solution of n-person games is proposed, based on the minimum deviation from statistical equilibrium subject to the constraints imposed by the group rationality and individual rationality. The new solution is compared with the Shapley value and von Neumann-Morgenstern's core of the game in the context of the 15-person game of passing and defeating resolutions in the UN Security Council involving five permanent members and ten nonpermanent members. A coalition classification, based on the minimum ramification cost induced by the characteristic function of the game, is also presented.
ENTROPY OF DISCRETE FUZZY MEASURES
Authors: MARICHAL JEAN-LUC , ROUBENS MARC
Published: April 2003

The concept of entropy of a discrete fuzzy measure has been recently introduced in two different ways. A first definition was proposed by Marichal in the aggregation framework, and a second one by Yager in the framework of uncertain variables. We present a comparative study between these two proposals and point out their properties. We also propose a definition for the entropy of an ordinal fuzzy measure, that is, a fuzzy measure taking its values in an ordinal scale in the sense of measurement theory.
COHERENCE MEASURES ON FINITE FUZZY SETS
Authors: SANCHO-ROYO A. , VERDEGAY J. L.
Published: April 2003

Comparison tools for fuzzy sets are an indispensable topic. Mostly of this tools deal with fuzzy sets from the view of similarity, order and so forth. A comparison tool based on coherence intuitive concept is presented. For constructing this concept, one start from three basics properties. A development of this tool is presented, equally coherence measures are connected with Fishburn-Yager's ambiguity measures. Two methods for constructing coherence measures are shown: one from ambiguity measures and other from metrics on [0, 1]m. Concretely, has been constructed various coherence measures from different ambiguity measures and different metrics. Equivalency between some coherence measures has been shown. This paper finish with numeric examples presented in order to check coherence measures displayed.
BALANCED DISCRETE FUZZY MEASURES
Authors: CALVO T. , MARTIN J. , MAYOR G. , TORRENS J.
Published: April 2003

First a balancing property on a fuzzy measure is introduced. After that, the conditions of when an additive fuzzy measure is balanced are given and similar results are presented for 0-1 and S–decomposable fuzzy measures where S is a continuous t–conorm. Moreover, the concept of distance between two additive fuzzy measures is presented and some results related to the distance and the balancing property are developed.
DIVERGENCE MEASURES AND AGGREGATION OPERATIONS
Authors: MIRANDA P. , TORRES E. , GIL P.
Published: April 2003

In this paper we study the relations between divergence measures of two fuzzy sets and other well-known functions, namely aggregation operations and measures of fuzziness. We will show that these functions can be related. Therefore, we study some consequences of these properties as an application; indeed, we obtain some special cases of divergence measures whenever the aggregation operation fulfils some properties. Another application is the translation of some properties of divergence measures to measures of fuzziness.
COMPOSITIONS OF FUZZY RELATIONS BASED ON AGGREGATION OPERATOR AND ITS PSEUDOCOMPLEMENT
Authors: PORTILLA MIREN I. , BURILLO PEDRO
Published: April 2003

The main aim of this paper is to present the properties of the (sup-)composition based on a general aggregation operator defined with the most useful conditions and analyze some properties about the pseudocomplement (associated with the aggregation) and the (inf-)composition based on it, to show that these compositions have analogous properties to the based on t-norms.
INTEGRATION WITH RESPECT TO DECOMPOSABLE MEASURES, BASED ON A CONDITIONALLY DISTRIBUTIVE SEMIRING ON THE UNIT INTERVAL
Authors: KLEMENT ERICH PETER , MESIAR RADKO , PAP ENDRE
Published: April 2003

To cover almost all known Lebesgue type integrals constructed by means of pseudo-operations, the (S, U)-integral based on a t-conorm S, a uninorm (or t-norm) U and an S-measure (decomposable measure) is introduced and its properties are studied. Also its relationship to aggregation operators is discussed.
REPRESENTATION OF PREFERENCE RELATIONS INDUCED BY LATTICE-VALUED, GENERALIZED POSSIBILISTIC UTILITY FUNCTIONS
Authors: ZAPICO ADRIANA , GODO LLUIS
Published: April 2003

Representational issues of preferences in the framework of a possibilistic ordinal decision model under uncertainty were introduced by Dubois and Prade a few years ago. In this framework, finite, linear, commensurate uncertainty and preference scales are assumed and decisions are ranked according to their expected utility in terms of Sugeno integrals. In this paper we generalise the model by allowing (i) to measure uncertainty and preferences on finite, distributive lattices with involution, and (ii) to formulate the utility expectations in terms of generalized Sugeno integrals where t-norms and t-conorms play a role. For these generalized utility functions we provide axiomatic characterisations. Finally, we also briefly comment the case of working with belief states that may be partially inconsistent, which is usual in case-based decision making problems or when several inconsistent sources of information are available.
FUZZY CLUSTERING WITH WEIGHTING OF DATA VARIABLES
Authors: KELLER ANNETTE , KLAWONN FRANK
Published: April 2003

We introduce an objective function-based fuzzy clustering technique that assigns one influence parameter to each single data variable for each cluster. Our method is not only suited to detect structures or groups of data that are not uniformly distributed over the structure's single domains, but gives also information about the influence of individual variables on the detected groups. In addition, our approach can be seen as a generalization of the well-known fuzzy c-means clustering algorithm.
A MULTIPLE CLASSIFIER SYSTEM USING AMBIGUITY REJECTION FOR CLUSTERING-CLASSIFICATION COOPERATION
Authors: GUNES VEYIS , MENARD MICHEL , LOONIS PIERRE
Published: April 2003

This article aims at showing that supervised and unsupervised learnings are not competitive, but complementary methods. We propose to use a fuzzy clustering method with ambiguity rejection to guide the supervised learning performed by bayesian classifiers. This method detects ambiguous or mixed areas of a learning set. The problem is seen from the multi-decision point of view (i.e. several classification modules). Each classification module is specialized on a particular region of the feature space. These regions are obtained by fuzzy clustering and constitute the original data set by union. A classifier is associated with each cluster. The training set for each classifier is then defined on the cluster and its associated ambiguous clusters. The overall system is parallel, since different classifiers work with their own training data clusters. The algorithm makes possible the adaptive classifier selection in the sense that the fuzzy clustering with ambiguity rejection gives adapted training data regions of the feature space. The decision making is the fusion of outputs from the most adapted classifiers.
A DECOMPOSITION OF k-ADDITIVE CHOQUET AND k-MAXITIVE SUGENO INTEGRALS
Authors: KIM CAO-VAN , DE BAETS BERNARD
Published: April 2003

Previous work has shown that the Choquet integral w.r.t. a symmetric k-order additive fuzzy measure is characterized as a weighted sum, with possibly negative weights, of k specific OWA operators, and that the Sugeno integral w.r.t. a symmetric k-order maxitive fuzzy measure is characterized as a weighted maximum of k order statistics. In this paper, these characterizations are extended to the general, non-symmetric case, thereby providing additional insight in the symmetric case. More specifically, a new general decomposition of the Choquet integral w.r.t. a k-order additive fuzzy measure and of the Sugeno integral w.r.t. a k-order maxitive fuzzy measure are established.
HOW TO IMPROVE ACTS: AN ALTERNATIVE REPRESENTATION OF THE IMPORTANCE OF CRITERIA IN MCDM
Authors: GRABISCH MICHEL , LABREUCHE CHRISTOPHE
Published: April 2003

The intepretation of aggregation functions in multicriteria decision making is often based on indices such as importance indices that measure the importance of one criterion. For instance, for the Choquet integral, the importance index is the so-called Shapley value. The use of an index must always be limited to the specific context it has been designed for. Here, we are interested in determining on which criteria acts should be improved if we want their global evaluation to increase as much as possible. The Shapley value is not suited for describing this. So, we introduce a new index of importance which represents the mean worth for acts to reach higher scores in a set of criteria. This index is defined for general aggregation functions with the help of several axioms. This importance index is then applied to the Choquet integral. In particular, we computer the worth to reach higher levels in one attribute, and in a couple of attributes. Interestingly, this leads to quantities that are closely related to the Shapley and interaction indices.
PSEUDO-INTEGRAL BASED ON NON-ASSOCIATIVE AND NON-COMMUTATIVE PSEUDO-ADDITION AND PSEUDO-MULTIPLICATION
Authors: PAP ENDRE , ŠTAJNER-PAPUGA IVANA
Published: April 2003

We shall consider non-associative and non-commutative pseudo-addition and pseudo-multiplication, i.e., generalized pseudo-operations. More precise, we shall consider special class of generalized pseudo-operations that have the following form: x⊕ y=k-1(ε k(x)+k(y)), x⊙ y=k-1(k(x)ε k(y)), where ε is arbitrary fixed positive real number and k is a positive strictly monotone function. Using previous pseudo-operations, corresponding pseudo-measure and pseudo-integral will be introduced. Pseudo-convolution based on pseudo-measure and pseudo-integral will be constructed.
RET OPERATORS GENERATED BY TRIANGULAR NORMS AND COPULAS
Authors: ŠABO MICHAL , KOLESÁROVÁ ANNA , VARGA ŠTEFAN
Published: April 2003

In the paper the possibility of the construction of relevancy transformation operators introduced in 9 by means of triangular norms and copulas is studied. Several examples are included.
WEIGHTED MEANS BASED ON TRIANGULAR CONORMS
Authors: CALVO TOMASA , MESIAR RADKO
Published: April 2003

Generalizing the construction of weighted quasi–arithmetic means from generated t–conorms, we propose a new class of weighted means related to continuous t–conorms. By duality, t–norm based weighted means can be obtained, too. Our method fits also in the case of finite ordinal scales. Several examples are given.
AGGREGATION OPERATORS AND ASSOCIATED FUZZY MEASURES
Authors: BENVENUTI PIETRO , VIVONA DORETTA , DIVARI MARIA
Published: April 2003

The natural properties of the aggregation operators and the most elementary ones are the idempotence, the monotonicity and the continuity from below. We assume only these properties for the aggregation operators with infinitely many inputs, defined by functionals on the family of measurable functions. A family of fuzzy measures is associated with each aggregation operator. The properties of horizontal or vertical pseudo-additivity are recognizable by means of this family of fuzzy measures.
AGGREGATION OPERATORS AND ADDITIVE GENERATORS
Authors: KOMORNÍKOVÁ MAGDA
Published: April 2003

Generated aggregation operators on continuous and discrete scales derived by means of a generating system are introduced. Linear generating systems are shown to be equivalent with the class of weighted means. The following classes are characterized: symmetric generated aggregation operators, idempotent generated aggregation operators, generated aggregation operators with a neutral element. Several examples are included.
COLLAPSED INPUT-BASED AGGREGATION
Authors: KOLESÁROVÁ ANNA
Published: April 2003

Collapsed input-based aggregation leading to constrained aggregation operators is discussed. Constrained aggregation operators eliminating a non–distinguishing evaluation are studied. Moreover, collapse invariant aggregation operators are defined and a complete characterization of symmetric collapse invariant aggregation operators, which are independent of the position of the collapsed input, is given. Several examples are included.
ON A CLASS OF DISTRIBUTIVE FUZZY IMPLICATIONS
Authors: BACZYŃSKI MICHAŁ
Published: April 2003

We deal with the system of functional equations I(x,T(y,z))=T(I(x,y), I(x,z)), I(x,I(y,z))=I(T(x,y),z), where function T:[0,1]2→ [0,1] is a strict t-norm and I:[0,1]2→ [0,1] is an unknown function. Under some assumptions imposed on function I we obtain that I is almost conjugate with the Yager fuzzy implication.
THE NECESSITY OF THE STRONG α-CUTS OF A FUZZY SET
Authors: COUSO INÉS , MONTES SUSANA , GIL PEDRO
Published: April 2003

Some aspects of the relationship between Goodman and Nguyen's one-point coverage interpretation of a fuzzy set and Zadeh's possibilistic interpretation are discussed. As a result of this, we derive a new interpretation of the strong α-cut of a normalized fuzzy set, namely that of being the most precise set we are sure to contain an unknown parameter with probability greater than or equal to 1-α.
BELL-TYPE INEQUALITIES IN FUZZY PROBABILITY CALCULUS
Authors: PYKACZ JAROSŁAW , D'HOOGHE BART
Published: April 2003

Bell-type inequalities, used in mathematical physics as a criterion to check whether a physical situation allows description in terms of classical (Kolmogorovian) or quantum probability calculus are applied to various fuzzy probability models. It occurs that the standard set of Bell-type inequalities does not allow to distinguish Kolmogorovian probabilities from fuzzy probabilities based on the most frequently used Zadeh intersection or probabilistic intersection, but it allows to distinguish all these models from fuzzy probability models based on Giles (Łukasiewicz) intersection. It is proved that if we use fuzzy set intersections pointwisely generated by Frank's fundamental triangular norms Ts(x,y), then the borderline between fuzzy probability models that can be distinguished from Kolmogorovian ones and these fuzzy probability models that cannot be distinguished is for [Formula: see text].
SPEAKER ADAPTATION OF FUZZY-PERCEPTRON-BASED SPEECH RECOGNITION
Authors: Lin Chin-Teng , Nein Hsi-Wen , Lin Wei-Fen
Published: April 2003

In this paper, we propose a speech recognition algorithm which utilizes hidden Markov models (HMM) and Viterbi algorithm for segmenting the input speech sequence, such that the variable-dimensional speech signal is converted into a fixed-dimensional speech signal, called TN vector. We then use the fuzzy perceptron to generate hyperplanes which separate patterns of each class from the others. The proposed speech recognition algorithm is easy for speaker adaptation when the idea of "supporting pattern" is used. The supporting patterns are those patterns closest to the hyperplane. When a recognition error occurs, we include all the TN vectors of the input speech sequence with respect to the segmentations of all HMM models as the supporting patterns. The supporting patterns are then used by the fuzzy perceptron to tune the hyperplane that can cause correct recognition, and also tune the hyperplane that resulted in wrong recognition. Since only two hyperplane need to be tuned for a recognition error, the proposed adaptation scheme is time-economic and suitable for on-line adaptation. Although the adaptation scheme cannot ensure to correct the wrong recognition right after adaptation, the hyperplanes are tuned in the direction for correct recognition iteratively and the speed of adaptation can be adjusted by a "belief" parameter set by the user. Several examples are used to show the performance of the proposed speech recognition algorithm and the speaker adaptation scheme.
t–OPERATORS
Authors: MAS M. , MAYOR G. , TORRENS J.
Published: April 2003

This paper looks over a class of operators introduced in ([2]), called t–operators. Introduced in order to be applied to fuzzy preorders, their properties lead them to be also appropriate in some fields like aggregation problems and expert systems. We characterize these operators as a special combination of a t-norm and a t-conorm on [0, 1] in a similar way of uninorms in ([5]). We study duality and self duality on t–operators with respect to a strong negation N. We also give a classification of continuous t–operators through ordinal sums. Finally, we obtain from some t–operators (those idempotent) a special kind of E.A.F. by extending them to E=∪n≥1[0,1]n.
MAXIMUM ENTROPY PRINCIPLE AND THE LOGISTIC MODEL
Authors: LEBLANC RAYMOND , SHAPIRO STANLEY
Published: April 2003

This paper proposes the use of the maximum entropy principle to construct a probability model under constraints for the analysis of dichotomous data using the odds ratio adjusted for covariates. It gives a new understanding of the now famous logistic model. We show that we can do away with the hypothesis of linearity of the log odds and still effectively use the model properly. From a practical point of view, the result implies that we do not have to discuss the plausability of the linearity hypothesis relative to the data or the phenomenon under study. Hence, when using the logistic model, we do not have to discuss the multiplicative effect of the covariates on the odds ratio. This is a major gain in the use of the model if one does not have to establish or justify the multiplicative effect, for instance, of alcohol consumption while considering low birth weight babies.
MAXIMISING ENTROPY TO DEDUCE AN INITIAL PROBABILITY DISTRIBUTION FOR A CAUSAL NETWORK
Authors: MARKHAM MICHAEL J. , RHODES PAUL C.
Published: April 2003

The desire to use Causal Networks as Expert Systems even when the causal information is incomplete and/or when non-causal information is available has led researchers to look into the possibility of utilising Maximum Entropy. If this approach is taken, the known information is supplemented by maximising entropy to provide a unique initial probability distribution which would otherwise have been a consequence of the known information and the independence relationships implied by the network. Traditional maximising techniques can be used if the constraints are linear but the independence relationships give rise to non-linear constraints. This paper extends traditional maximising techniques to incorporate those types of non-linear constraints that arise from the independence relationships and presents an algorithm for implementing the extended method. Maximising entropy does not involve the concept of "causal" information. Consequently, the extended method will accept any mutually consistent set of conditional probabilities and expressions of independence. The paper provides a small example of how this property can be used to provide complete causal information, for use in a causal network, when the known information is incomplete and not in a causal form.
MULTIVARIATE NON-LINEAR FUZZY REGRESSION: AN EVOLUTIONARY ALGORITHM APPROACH
Authors: Buckley James J. , Feuring Thomas , Hayashi Yoichi
Published: April 2003

We first argue that a very important class of fuzzy functions in multivariate non-linear fuzzy regression is the multivariate fuzzy polynomials. Given some data, generated by a multivariate fuzzy function, our evolutionary algorithm searches our library of multivariate fuzzy polynomials for the one that best fits this data. Tests of our multivariate non-linear fuzzy regression package are given when the multivariate fuzzy function is a multivariate fuzzy polynomial and all the fuzzy numbers are non-negative.
FUZZY RELATIVE POSITION BETWEEN OBJECTS IN IMAGE PROCESSING: NEW DEFINITION AND PROPERTIES BASED ON A MORPHOLOGICAL APPROACH
Authors: BLOCH ISABELLE
Published: April 2003

In order to cope with the ambiguity of spatial relative position concepts, we propose a new definition of the relative position between two objects in a fuzzy set framework. This definition is based on a morphological and fuzzy pattern matching approach, and consists in comparing an object to a fuzzy landscape representing the degree of satisfaction of a directional relationship to a reference object. We detail its formal properties, and show that it is flexible and fits the intuition. Moreover, it applies also in 3D, and for fuzzy objects issued from images. It can be used for structural pattern recognition in images under imprecision.
GÖDEL REPRESENTABLE FUZZY WEAK ORDERS
Authors: DE BAETS BERNARD , FODOR JÁNOS , KERRE ETIENNE
Published: April 2003

This paper is devoted to the study of fuzzy weak orders, fuzzy quasi orders and fuzzy quasi-transitive relations in the context of group decision making. Transitivity is modelled by means of the minimum operator. In analogy to the numerical representation of classical weak orders, we consider a particular class of fuzzy weak orders that can be constructed from a numerical evaluation by means of Gödel implicator. We fully characterize the fuzzy relations that can be written as the intersection or union of a finite family of these so-called Gödel representable fuzzy weak orders.
POSSIBILISTIC SONAR DATA MODELING FOR MOBILE ROBOTS
Authors: DEMIRLI K. , MOLHIM M. , BULGAK A.
Published: April 2003

Sonar sensors are widely used in mobile robots applications such as navigation, map building, and localization. The performance of these sensors is affected by the environmental phenomena, sensor design, and target characteristics. Therefore, the readings obtained from these sensors are uncertain. This uncertainity is often modeled by using Probability Theory. However, the probablistic approach is valid when the available knowledge is precise which is not the case in sonar readings. In this paper, the behavior of sonar readings reflected from walls and corners are studied, then new models of angular uncertainty and radial imprecision for sonar readings obtained from corners and walls are proposed. These models are represented by using Possibility Theory, mainly possibility distributions.
THE LENGTH AND BETWEENNESS RELATIONS OF INDISTINGUISHABILITY OPERATORS
Authors: BOIXADER D. , JACAS J. , RECASENS J.
Published: April 2003

The most common ways used to generate indistinguishability operators, namely as transitive closure of reflexive and symmetric fuzzy relation, via the Representation Theorem and as decomposable relations, are related for archimedean t-norms introducing the notion of length of indistinguishability operators.
MENGER AND OVCHINNIKOV ON INDISTINGUISHABILITIES, REVISITED
Authors: TRILLAS ENRIC , CUBILLO SUSANA , CASTIÑEIRA ELENA
Published: April 2003

In his paper "Probabilistic Theories of Relations", Menger showed that, in some cases, Prod-Indistinguishabilities are the same as the antilogarithms of distances; later, Ovchinikov obtained a characterization for Prod-Indistinguishabilities.

In this note, Menger's result is included in a larger frame to obtain more Prod-Indistinguishabilities from distances, and Ovchinnikov's characterization is translated to distances in order to reach a larger class of them.
ON THE RELATION BETWEEN FUZZY PREORDERS AND FUZZY CONSEQUENCE OPERATORS
Authors: ELORZA J. , BURILLO P.
Published: April 2003

The purpose of this paper is to analyze the operators induced by relations and conversely the relations induced by operators in fuzzy logic. Given a t-norm * and given a non-empty universal set X, it is well known that if R is a fuzzy *-preorder on X then the operator induced by R, [Formula: see text], is a fuzzy consequence operator (FCO). In fact, [Formula: see text] is a *-coherent FCO. It is also known that if C is a *-coherent FCO then the relation induced by C, RC, is a fuzzy *-preorder. We explore the *-coherence axiom because we do not know in the literature any example of non-coherent operator. Then, several families of these operators will be shown. Moreover we prove that the equivalence between fuzzy preorders and fuzzy consequence operators is held in only one way. As a result, a characterization of the *-preorder concept using the induced operator is given. Also some characterizations which show when an operator induces a *-preorder are proved. Finally, we will show that the characterization of the operators induced by relations given for finite universes cannot be generalized for infinite universes.
LOCALLY INTERNAL AGGREGATION FUNCTIONS
Authors: MAYOR G. , MARTIN J.
Published: April 2003

We introduce the concept of locally internal aggregation function with domain ℝn and values in ℝ, and demonstrate some results which lead to the characterization of such functions.
LINGUISTIC REPRESENTATION OF FUZZY TEMPORAL PROFILES
Authors: FÉLIX PAULO , FRAGA SANTIAGO , BARRO SENÉN , MARÍN ROQUE
Published: April 2003

We take as a setting point the Fuzzy Temporal Profile (FTP) model, which is used to describe the temporal evolution of a certain physical parameter. This model defines the approximation of an evolution curve by means of a set of linear sections between a series of significant points (X0, X1, …, XN), and in which each section is defined by means of an imprecise constraint on the duration, the increase in value and the slope between the points connected by the section. Following the FTP model we present a language for the representation of trends, the semantics of which is projected onto a fuzzy definition of each one of the constraints of a profile of interest.
A STUDY ABOUT THE INCLUSION OF LINGUISTIC HEDGES IN A FUZZY RULE LEARNING ALGORITHM
Authors: GONZÁLEZ A. , PÉREZ R.
Published: April 2003

A very important problem associated with the use of learning algorithms consists of fixing the correct assignment of the initial domains for the predictive variables. In the fuzzy case, this problem is equivalent of define the fuzzy labels for each variable. In this work, we propose the inclusion in a learning algorithm, called SLAVE, of a particular kind of linguistic hedges as a way to modify the intial semantic of the labels. These linguistic hedges allow us both to learn and to tune fuzzy rules.
A TOTAL ORDER FOR THE GRADED NUMBERS USED IN DECISION PROBLEMS
Authors: HERENCIA JOSÉ A. , LAMATA M. TERESA
Published: April 2003

Let us consider a classical problem of decision-making with fuzzy rewards. In order to choose the alternative which corresponds to the best fuzzy reward, we need to use a total order for the fuzzy numbers involved in the problem. In this paper, we consider a definition of such a total order, which is based upon two subjective aspects: the degree of optimism/pessimism and the liking for risk/safety. We also use the graded numbers which are analogous to the fuzzy numbers. However, the operations with graded numbers are carried out as a simple extension of operations with real intervals.
SCATTERING PATH FORMALISM FOR THE PROPAGATION OF INTERACTING COMPOUNDS IN ORDERED AND DISORDERED MATERIALS
Authors: BERAKDAR J.
Published: April 2003

This study presents a theoretical framework for the propagation of a compound consisting of N interacting particles in a multicenter potential. A novel Green operator approach is proposed that disentangles the geometrical and dynamical properties of the scatterers from the internal evolution of the projectile compound. Furthermore, the transition operator for the scattering from the multicenter potential is expanded in terms of many-body scattering path operators, which in turn are expressed in terms of single site transition operators that are amenable to computations. To deduce the correlated many-body Green operator of the scattering compound, a cumulative method is designed that reduces the problem to the evaluation of Green operators of systems with a reduced number of interacting particles. This is particularly useful for efficient calculations and encompasses the usual perturbative approaches.
A COMPARISON OF ANGULAR BEHAVIORS AMONG ELECTRON AND POSITRON SCATTERING FACTORS
Authors: TONG S. Y. , MOK C. W.
Published: April 2003

In this review, we discuss the angular anisotropies in the scattering factors of electrons and positrons for scattering by atoms in solids. We show that, as a function of the angle, the maximum number of dips in the scattering factor's magnitude and jumps of near π in its phase are related to the angular momenta of the bound and resonance states of the potential. The effect of the scattering factor's anisotropies on low-energy electron and positron holographic wave-front reconstruction is discussed.