fora a fuzzy set based framework for online reputation management the social web offers increasingly simple ways to publish and disseminate personal or opinionated information which can rapidly exhibit a disastrous influence on the online reputation of organizations based on social web data this study describes the building of an ontology based on fuzzy sets at the end of a recurring harvesting of folksonomies by web agents the aggregated tags are purified linked and transformed to a so called fuzzy grassroots ontology by means of a fuzzy clustering algorithm this self updating ontology is used for online reputation analysis a crucial task of reputation management with the goal to follow the online conversation going on around an organization to discover and monitor its reputation in addition an application of the fuzzy online reputation analysis fora framework lessons learned and potential extensions are discussed in this article

new finite elements with embedded strong discontinuities for the modeling of failure in electromechanical coupled solids this paper presents new finite elements with embedded strong discontinuities in the form of jumps in the mechanical displacement field as well as jumps in the electric potential for the modeling of failure in electromechanical coupled solids such materials which are commonly used in smart systems in the form of actuators or sensors are prone to defects in the form of cracks represented by such strong discontinuities in this work a discrete account of the individual jumps is made with the possibility of their propagation through the individual finite elements without the need of remeshing or refinement strategies originated for purely mechanical based materials and commonly referred as the strong discontinuity approach an extension to account for the electromechanical coupling and the additional jumps in the electric potential is made in this work the decomposition of that methodology into a global problem representing here the electromechanical boundary value problem and a local problem through which the strong discontinuities are introduced serves convenient when developing the corresponding finite elements based on the requirement to avoid stress locking phenomena this idea is extended in this work to develop new finite elements based on the incorporation of electrical separation modes directly into the discrete formulation keeping its local and computational efficient property with regard to the storage and possible static condensation of the parameters used to describe the mechanical and electrical discontinuities on a constitutive level the mechanical traction separation law is extended to account for a softening type behavior in the relation between the normal component of the electric displacement field and the surface charge density this is accomplished through the derivation of a localized electromechanical damage model based on the principle of maximum damage dissipation the performance of the resulting new finite elements is illustrated with several numerical simulations including a compact tension test and a three point bending test of piezoelectric ceramics and compared with experimental results available in the literature

an analysis of strong discontinuities in multiplicative finite strain plasticity and their relation with the numerical simulation of strain localization in solids abstract this paper presents an analysis of strong discontinuities in inelastic solids at finite strains solutions exhibiting this type of discontinuities characterized by a discontinuous displacement field are shown to make physical and mathematical sense in a classical multiplicative plasticity continuum model if the softening modulus is reinterpreted as a singular distribution physically the strainsoftening is localized along the discontinuity conditions for the appearance of strong discontinuities in the geometrically nonlinear range are characterized as it is the response of the material during localization in addition these analytical results are exploited in the design of a new class of finite element methods the proposed methods fall within the class of enhanced strain methods and lead to solutions independent of the mesh size and insensitive to mesh alignment without requiring any regularization of the solutions by numerical parameters like a characteristic length

computing exact permutation p values for association rules association rule mining is an important task in the field of data mining and many efficient algorithms have been proposed to address this problem however a large portion of the rules reported by these algorithms just satisfy the user defined constraints purely by accident and those that are not statistically meaningful should be filtered out through statistical significance testing in the context of association rule discovery the permutation based approach can achieve better performance than other competitive methods although several drawbacks of this effective approach narrow its usability in this paper we provide an analysis of these disadvantages and propose an algorithm called exact permutation p values for association rules epar to calculate the exact p values of all tested rules experiments on different types of data sets demonstrate that epar can successfully alleviate the disadvantages and outperform the direct permutation based method over several performance measures

examples counterexamples and measuring fuzzy associations this paper examines the measurement of the degree to which tuples in a database support a relation among attributes based on a comparison of the number of examples and counterexamples of the relation in particular we are concerned with associations that represent imprecise constraints placed upon the value of one attribute by those of other attributes associations of this form may be described by fuzzy rules and the analysis requires an assessment of the degree to which a tuple satisfies the imprecise constraint specified by the rule standard measures of rule validity are extended to fuzzy associations based on the degree that the tuples are examples counterexamples or irrelevant to imprecise relations a scaling of the relevance of a tuple is proposed to minimize the impact of the accumulation of small membership values on the confidence based validity measures

fuzzy association rules general model and applications the theory of fuzzy sets has been recognized as a suitable tool to model several kinds of patterns that can hold in data in this paper we are concerned with the development of a general model to discover association rules among items in a crisp set of fuzzy transactions this general model can be particularized in several ways each particular instance corresponds to a certain kind of pattern and or repository of data we describe some applications of this scheme paying special attention to the discovery of fuzzy association rules in relational databases

descent methods with linesearch in the presence of perturbations we consider the class of descent algorithms for unconstrained optimization with an armijo type stepsize rule in the case when the gradient of the objective function is computed inexactly an important novel feature in our theoretical analysis is that perturbations associated with the gradient are not assumed to be relatively small or to tend to zero in the limit as a practical matter we expect them to be reasonably small so that a meaningful approximate solution can be obtained this feature makes our analysis applicable to various difficult problems encounted in practice we propose a modified armijo type rule for computing the stepsize which guarantees that the algorithm obtains a reasonable approximate solution furthermore if perturbations are small relative to the size of the gradient then our algorithm retains all the standard convergence properties of descent methods

ten years of genetic fuzzy systems current framework and new trends fuzzy systems have demonstrated their ability to solve different kinds of problems in various application domains currently there is an increasing interest to augment fuzzy systems with learning and adaptation capabilities two of the most successful approaches to hybridise fuzzy systems with learning and adaptation methods have been made in the realm of soft computing neural fuzzy systems and genetic fuzzy systems hybridise the approximate reasoning method of fuzzy systems with the learning capabilities of neural networks and evolutionary algorithms the objective of this paper is to provide an account of genetic fuzzy systems with special attention to genetic fuzzy rule based systems after a brief introduction to models and applications of genetic fuzzy systems the field is overviewed new trends are identified a critical evaluation of genetic fuzzy systems for fuzzy knowledge extraction is elaborated and open questions that remain to be addressed in the future are raised the paper also includes some of the key references required to quickly access implementation details of genetic fuzzy systems

mining numerical association rules via multi objective genetic algorithms association rule discovery is an ever increasing area of interest in data mining finding rules for attributes with numerical values is still a challenging point in the process of association rule discovery most of popular methods for association rule mining cannot be applied to the numerical data without data discretization there have been efforts to resolve the problem of dealing with numeric data these approaches suffer from problems which are discussed in this paper this work proposes a multi objective genetic algorithm approach for mining association rules for numerical data several measures are defined in order to determine more efficient rules three measures confidence interestingness and comprehensibility have been used as different objectives for our multi objective optimization which is amplified with genetic algorithms approach finally the best rules are obtained through pareto optimality this method is based on the notion of rough patterns that use rough values defined with upper and lower intervals to represent a range or set of values mutation and crossover operators give a powerful exploration ability to the method and allow it to find out the best intervals of existing numerical values the experimental results show that the generated rules by this method are more appropriate based on several different characteristics than the similar approaches results and our method outperforms these methods

remarks on convergence of the matrix splitting algorithm for the symmetric linear complementarity problem in this paper it is shown how to remove a restriction on the perturbation vectors h i imposed by mangasarian and luo and tseng in their respective convergence analyses of the matrix splitting algorithms

successive overrelaxation for support vector machines successive overrelaxation sor for symmetric linear complementarity problems and quadratic programs is used to train a support vector machine svm for discriminating between the elements of two massive datasets each with millions of points because sor handles one point at a time similar to platt s sequential minimal optimization smo algorithm 1999 which handles two constraints at a time and joachims svm sup light 1998 which handles a small number of points at a time sor can process very large datasets that need not reside in memory the algorithm converges linearly to a solution encouraging numerical results are presented on datasets with up to 10 000 000 points such massive discrimination problems cannot be processed by conventional linear or quadratic programming methods and to our knowledge have not been solved by other methods on smaller problems sor was faster than svm sup light and comparable or faster than smo

hydromechanical modeling of an initial boundary value problem studies of non uniqueness with a second gradient continuum a non uniqueness study for a hydromechanical boundary value problem is performed a fully saturated porous medium is considered using an elasto plastic constitutive equations to describe the mechanical behavior of the skeleton a real hydromechanical experiment which consists in a hollow cylinder test on a boom clay sample is modelled it is shown that the time step discretisation of the numerical problem has an effect on the initialisation of the newton raphson algorithm on a given time step different solutions for the same initial boundary value problem can consequently be found

three dimensional finite elements with embedded strong discontinuities to model material failure in the infinitesimal range summary this paper presents new three dimensional finite elements with embedded strong discontinuities in the small strain infinitesimal range the goal is to model localized surfaces of failure in solids such as cracks at fracture through enhancements of the finite elements that capture the propagating discontinuities of the displacement field in the element interiors in this way such surfaces of discontinuity can be sharply resolved in general meshes not necessarily related to the detailed geometry of the surface unknown a priori an important issue is also the consideration of general finite element formulations in the developments e g basic displacement based mixed or enhanced assumed strain finite element formulations as needed to optimally resolve the continuum problem in the bulk the actual modeling of the discontinuity effects including the incorporation of the cohesive law defining the discontinuity constitutive response is carried out at the element level with the proper enhancement of the discrete strain field of the element the added elemental degrees of freedom approximate the displacement jumps associated with the discontinuity and are defined independently from element to element thus allowing their static condensation at the element level without affecting the global mechanical problem in terms of the number and topology of the global degrees of freedom in fact this global local structure of the finite element methods developed in this work arises naturally from a multi scale characterization of these localized solutions with the discontinuities understood to appear in the small scales thus leading directly to these computationally efficient numerical methods for their numerical resolution easily incorporated to an existing finite element code the focus in this paper is on the development of finite elements incorporating a linear interpolation of the displacement jumps in the general three dimensional setting these interpolations are shown to be necessary for hexahedral elements to avoid the so called stress locking that occurs with simpler constant approximations of the jumps namely a spurious transfer of stresses across the discontinuity not allowing its full release and hence resulting in an overstiff or locked numerical solution the design of the new finite elements is accomplished in this work by a direct identification of the separation modes to be incorporated in the discrete strain field of the element rather than from an assumed discontinuous interpolation of the displacements assuring with this approach their locking free response by design an additional issue addressed in the paper is the geometric characterization and propagation of the discontinuity surfaces in the general three dimensional setting of interest here the paper includes a series of numerical simulations illustrating and evaluating the properties of the new finite elements copyright 2012 john wiley sons ltd

an algorithm based on incompatible modes for the global tracking of strong discontinuities in shear localization analyses abstract numerical methods for predicting localized shear failure in elasto plastic solids have experienced considerable advancements in the last decades among these approaches the so called embedded strong discontinuity esd method is often successfully used to accurately simulate the post localization response with negligible dependence on the finite element discretization however it was observed that the employed discontinuity tracking strategy plays a crucial role in the successful localization analysis in this contribution we propose a novel strategy for the global tracking of discontinuity surfaces it is based on exploiting information obtained from the enhanced parameters employed in enhanced assumed strain eas formulations it is well known that enhanced strain element formulations are able to better capture localized shear deformations as compared to standard finite elements this can be explained as a consequence of the improved performance in bending we observed that the approximation of the strain jumps delimiting the shear band is connected with a deformation field characterized by opposite bending curvatures across these two discontinuities hence in view of the relations existing between the kinematics of strong and weak discontinuities we formulate a proper scalar function of the enhanced parameters to identify potential strong discontinuity surfaces which are evaluated in each step of the analysis with negligible computational cost this proposed approach has a global character as it is based upon evaluating discontinuity surfaces defined in the complete analysis domain that are by construction continuous across elements we demonstrate that the tracking algorithm correctly identifies the potential strong discontinuity surface already in early loading stages even before a localization condition is fulfilled in those elements which are crossed by the potential failure surface and which also satisfy the localization condition the kinematics of embedded strong discontinuities is activated to capture the shear failure surface the performance of the new tracking algorithm is demonstrated by means of several numerical shear localization analyses using associative and non associative drucker prager elastoplastic models to simulate 2 d and 3 d benchmarkanalyses

an analysis of strong discontinuities in a saturated poro plastic solid we present in this paper an analysis of strong discontinuities in fully saturated porous media in the infinitesimal range in particular we describe the incorporation of the local effects of surfaces of discontinuity in the displacement field and thus the singular distributions of the associated strains from a local constitutive level to the large scale problem characterizing the quasi static equilibrium of the solid the characterization of the flow of the fluid through the porous space is accomplished in this context by means of a localized singular distribution of the fluid content that is involving a regular fluid mass distribution per unit volume and a fluid mass per unit area of the discontinuity surfaces in the small scale of the material this framework is shown to be consistent with a local continuum model of coupled poro plasticity with the localized fluid content arising from the dilatancy associated with the strong discontinuities more generally complete stress displacement fluid content relations are obtained along the discontinuities thus identifying the localized dissipative mechanisms characteristic of localized failures of porous materials the proposed framework also involves the coupled equation of conservation of fluid mass and seepage through the porous solid via darcy s law and considers a continuous pressure field with discontinuous gradients thus leading to discontinuous fluid flow vectors across the strong discontinuities all these developments are then examined in detail for the model problem of a saturated shear layer of a dilatant material enhanced finite element methods are developed in this framework for this particular problem the finite elements accommodate the different localized fields described above at the element level several representative numerical simulations are presented illustrating the performance of the proposed numerical methods copyright 1999 john wiley sons ltd

new finite elements with embedded strong discontinuities in the finite deformation range this paper develops new finite elements with embedded strong discontinuities for the modeling of the failure of solids in the finite deformation range the cases of interest include cracks shear bands delamination in composites and similar failures modeled by a propagating discontinuity in the deformation mapping that incorporates a cohesive law in terms of the associated displacement jumps the new elements accommodate the discontinuity in their interiors with a linear interpolation of the displacement jumps in contrast to the existing elements with constant jumps a general methodology is proposed for the development of such finite elements but the final focus is on quadrilateral elements for plane problems where a constant jump interpolation leads to a spurious transfer of stresses through the discontinuity or stress locking in certain common configurations the key aspect of the new elements is the proper enhancement of the deformation gradient that can represent correctly the kinematics of linearly separating discontinuities including a relative finite rotation across the discontinuity and in a frame indifferent manner the enhanced parameters modeling the displacement jumps are introduced independently for each element allowing for their static condensation at the element level and hence to arrive at a global system of equations with the same number and connectivity of the original global degrees of freedom for the underlying finite element mesh this situation leads to a particularly simple implementation of the proposed approach in an existing finite element code the performance of the new elements is illustrated with several numerical simulations including delamination in composite materials and propagating shear bands in a finitely deforming elastoplastic solid

fuzzy c p means clustering and its application to a fuzzy rule based classifier toward good generalization and good interpretability this paper introduces a new classifier design method based on a modification of the classical fuzzy c means clustering first a new fuzzy c means clustering with p constant prototypes is proposed this method can be considered a generalization of the concept of the conditional fuzzy clustering with some prototypes a priori known a special initialization of the prototypes is introduced next the proposed clustering method is used to construct the premises of an if then rule based classifier the conclusions of these rules are obtained by minimization of a criterion function with various approximations of a misclassification error e g based on the quadratic the linear the sigmoidal or the huber s loss function the conjugate gradient algorithm is used to minimize the proposed criterion function each if then rule is represented in the mamdani assilan form which has good interpretability finally an extensive experimental analysis on 14 benchmark datasets is performed to demonstrate the validity of the classifier introduced its competitiveness to the state of the art classifiers with respect to both performance and interpretability is also shown

genetic algorithm based framework for mining fuzzy association rules it is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining simply because characteristics of quantitative data are in general unknown besides it is unrealistic that the most appropriate fuzzy sets can always be provided by domain experts motivated by this in this paper we propose an automated method for mining fuzzy association rules for this purpose we first present a genetic algorithm ga based clustering method that adjusts centroids of the clusters which are to be handled later as midpoints of triangular membership functions next we give a different method for generating the membership functions by using clustering using representatives cure clustering algorithm which is known as one of the most efficient clustering algorithms described in the literature finally we compared the proposed ga based approach with other approaches from the literature experiments conducted on 100k transactions from the us census in the year 2000 show that the proposed method exhibits a good performance in terms of execution time and interesting fuzzy association rules

generalized weighted conditional fuzzy clustering fuzzy clustering helps to find natural vague boundaries in data the fuzzy c means method is one of the most popular clustering methods based on minimization of a criterion function among many existing modifications of this method conditional or context dependent c means is the most interesting one in this method data vectors are clustered under conditions based on linguistic terms represented by fuzzy sets this paper introduces a family of generalized weighted conditional fuzzy c means clustering algorithms this family include both the well known fuzzy c means method and the conditional fuzzy c means method performance of the new clustering algorithm is experimentally compared with fuzzy c means using synthetic data with outliers and the box jenkins database

embedded localization band in undrained soil based on regularized strong discontinuity theory and fe analysis abstract the paper presents a novel approach to the analysis of a developing localization zone in undrained soil considered as a mixture of a solid skeleton and fluid filled pores where the solid phase is considered as elastic plastic the basic feature is the concept of regularized displacement and pore pressure discontinuities which are assumed to occur across an internal discontinuity surface in this respect the present developments are extensions of those suggested by simo et al 1993 comput mech 12 277 296 and more recently by larsson and runesson 1995 j engng mech asce in press a finite element formulation is proposed on the basis of a mixed variational formulation in the spirit of the enhanced strain concept by simo and rifai 1990 int j numer meth engng 29 1595 1638 in this fashion the localization zone is embedded into a base element for the ordinary analysis of the non localized mixture problem

strain localization in frictional materials exhibiting displacement jumps abstract this paper presents a mathematical model for analyzing strain localization in frictional solids exhibiting displacement jumps precise conditions for the appearance of slip lines including their initiation and evolution are outlined for a rate independent strain softening drucker prager model and explicit analytical expressions are used to describe the orientation of the slip line a stress displacement relation obtained through the consistency condition is also formulated to describe the quasi static response in the post localization regime the mathematical model which is cast within the framework of finite element analysis employing the assumed enhanced strain method circumvents mesh dependence issues often associated with rate independent plasticity models it is shown that the enhancement equation is nothing else but the consistency condition imposed on the band numerical examples involving plane strain compression are described to demonstrate objectivity with respect to mesh refinement and insensitivity to mesh alignment of finite element solutions

multi objective rule mining using genetic algorithms association rule mining problems can be considered as a multi objective problem rather than as a single objective one measures like support count comprehensibility and interestingness used for evaluating a rule can be thought of as different objectives of association rule mining problem support count is the number of records which satisfies all the conditions present in the rule this objective gives the accuracy of the rules extracted from the database comprehensibility is measured by the number of attributes involved in the rule and tries to quantify the understandability of the rule interestingness measures how much interesting the rule is using these three measures as the objectives of rule mining problem this article uses a pareto based genetic algorithm to extract some useful and interesting rules from any market basket type database based on experimentation the algorithm has been found suitable for large databases

finite element analysis of localization of deformation and fluid pressure in an elastoplastic porous medium abstract the paper concerns the issue of progressive development of shear bands in the problem of coupled deformation and fluid diffusion in porous media the governing continuum equations are based on porous media theory applied to an elastic plastic solid skeleton at small deformations in the localization analysis the concept of regularized discontinuity is extensively used at the application to the conservation laws of momentum and mass as a result we obtain a coupled localization condition that is preserved also in the numerical formulation attention is also given to the design of an overall numerical algorithm to solve the coupled set of non linear finite element equations that arise from the element embedded band approach in order to arrive at the proper design of the algorithm we resort to a staggering between the continuous global problem and the discontinuous element problems in the numerical examples the algorithm is shown to be able to capture onset of localization as well as the progressive development of shear bands in the examples we study the influence of local and global boundary drainage conditions and the internal friction angle to the failure mechanisms

aes for multiscale localization modeling in granular media this work presents a multiscale strong discontinuity approach to tackle key challenges in modeling localization behavior in granular media accommodation of discontinuities in the kinematic fields and direct linkage to the underlying grain scale information assumed enhanced strain aes concepts are borrowed to enhance elements for post localization analysis but are reformulated within a recently proposed hierarchical multiscale computational framework unlike classical aes methods where material properties are usually constants or assumed to evolve with some arbitrary phenomenological laws this framework provides a bridge to extract evolutions of key material parameters such as friction and dilatancy based on grain scale computational or experimental data more importantly the phenomenological softening modulus typically used in aes methods is no longer required numerical examples of plane strain compression tests are presented to illustrate the applicability of this method and to analyze its numerical performance

rederivation of the fuzzypossibilistic clustering objective function through bayesian inference unsupervised clustering of a set of datums into homogeneous groups is a primitive operation required in many signal and image processing applications in fact different incarnations and hybrids of fuzzy c means fcm and possibilistic c means pcm have been suggested which address additional requirements such as accepting weighted sets and being robust to the presence of outliers nevertheless arriving at a general framework which is independent of the datum model and the notion of homogeneity of a particular problem class is a challenge however this process has not been followed organically and clustering algorithms are generally based on exogenous objective functions which are heuristically engineered and are believed to lead to the satisfaction of a required behavior these techniques also commonly depend on regularization coefficients which are to be set prudently by the user or through separate processes in contrast in this work we utilize bayesian inference and derive a robustified objective function for a fuzzypossibilistic clustering algorithm by assuming a generic datum model and a generic notion of cluster homogeneity we utilize this model for the purpose of cluster validity assessment as well we emphasize the epistemological importance of the theoretical basis on which the developed methodology rests at the end of this paper we present experimental results to exhibit the utilization of the developed framework in the context of four different problem classes

new error bounds and their applications to convergence analysis of iterative algorithms we present two new error bounds for optimization problems over a convex set whose objective function f is either semianalytic or strictly convex with 1 we then apply these error bounds to analyze the rate of convergence of a wide class of iterative descent algorithms for the aforementioned optimization problem our analysis shows that the function sequence f xk converges at least at the sublinear rate of k for some positive constant where k is the iteration index moreover the distances from the iterate sequence xk to the set of stationary points of the optimization problem converge to zero at least sublinearly

improved versions of assumed enhanced strain tri linear elements for 3d finite deformation problems abstract improved three dimensional tri linear elements for finite deformation problems are developed based on an assumed enhanced strain methodology which in the linear regime incorporates the classical method of incompatible modes as a particular case three crucial modifications of a recently proposed element which reduces to wilson s brick in the linear regime are introduced to prevent locking response in distorted configurations and to maintain proper rank while preserving excellent performance in bending dominated and localization problems i a modified quadrature rule ii an additional enhancement of the divergence term and iii a modification of the isoparametric shape function derivatives for the three dimensional problem moreover these modified shape function derivatives are shown to improve the performance of the standard tri linear brick in distorted configurations in addition a strategy is described to circumvent the memory storage requirements in the static condensation procedure of the enhanced strain parameters the excellent performance of the improved methodology is illustrated in representative numerical simulations

on linear convergence of iterative methods for the variational inequality problem abstract we present new linear convergence results for iterative methods for solving the variational inequality problem the methods include the extragradient method the proximal point method a matrix splitting method and a certain feasible descent method the proofs of the results are based on certain error bounds related to the algorithmic mappings moreover we show that all these error bounds hold if a projection type error bound holds

finite element methods for the analysis of strong discontinuities in coupled poro plastic media this paper presents the formulation of finite element methods for the numerical resolution of strong discontinuities in poro plastic solids fully coupled infinitesimal conditions are considered these solutions are characterized by a discontinuous displacement field with the associated singular strains and a singular distribution of the fluid content here singular distributions refer to dirac delta functions the singular component of the fluid content distribution models the fluid accumulated per unit area of the discontinuity surface and it is directly related with the dilatancy characterizing singular inelastic strains localized along such a surface it further accounts for a discontinuous fluid flow vector given by darcy s law in terms of a continuous pore pressure field all these considerations are incorporated in the proposed finite element methods through a local enhancement of the finite element interpolations as these discontinuities appear the local character of these interpolations lead after the static condensation of the enhanced fields to a large scale problem exhibiting the same structure as common finite element models of the global poro plastic problem but incorporating now crucially the localized dissipative effects characteristic of the localized failures several numerical simulations are presented to evaluate the performance of the proposed methods

rough fuzzy rule interpolation abstract fuzzy rule interpolation forms an important approach for performing inference with systems comprising sparse rule bases even when a given observation has no overlap with the antecedent values of any existing rules fuzzy rule interpolation may still derive a useful conclusion unfortunately very little of the existing work on fuzzy rule interpolation can conjunctively handle more than one form of uncertainty in the rules or observations in particular the difficulty in defining the required precise valued membership functions for the fuzzy sets that are used in conventional fuzzy rule interpolation techniques significantly restricts their application in this paper a novel rough fuzzy approach is proposed in an attempt to address such difficulties the proposed approach allows the representation handling and utilisation of different levels of uncertainty in knowledge this allows transformation based fuzzy rule interpolation techniques to model and harness additional uncertain information in order to implement an effective fuzzy interpolative reasoning system final conclusions are derived by performing rough fuzzy interpolation over this representation the effectiveness of the approach is illustrated by a practical application to the prediction of diarrhoeal disease rates in remote villages it is further evaluated against a range of other benchmark case studies the experimental results confirm the efficacy of the proposed work

fuzzy set technology in knowledge discovery abstract fuzzy models are constructs relying heavily both on a qualitative domain knowledge and diverse optimization techniques what makes them different from other models is their inherent embedding in the context of nonnumeric set or fuzzy set oriented information one can also look at the development of the fuzzy models from the perspective of data mining a prudent and user oriented sifting of data qualitative observations and calibration of commonsense rules in an attempt to establish meaningful and useful relationships between system s variables the role of fuzzy sets in knowledge discovery has not been visible even though they are inherently inclined towards coping with linguistic domain knowledge the paper re examines the key issues of knowledge discovery by putting them in the context of the technology of fuzzy sets subsequently we reveal several interesting links between fuzzy data mining and fuzzy sets the study is also geared toward a knowledge oriented and context based modification of well known fuzzy clustering

representation by levels an alternative to fuzzy sets for fuzzy data mining abstract in this paper we describe and discuss the main contributions of the representation by levels approach to fuzzy data mining representation by levels is an alternative representation of fuzziness in information and data which is complementary to fuzzy sets in the sense that it provides tools and algebraic structures beyond the capabilities of fuzzy set theories based on t norms t conorms and fuzzy negations our approach allows to extend any crisp mining technique to the fuzzy case in a simple way keeping all the properties of the crisp technique we illustrate our discussion with examples and existing approaches based on representation by levels to fuzzy association rules and the related issues of mining exception anomalous rules and mining fuzzy bag databases

fuzzy j means a new heuristic for fuzzy clustering abstract a fuzzy clustering problem consists of assigning a set of patterns to a given number of clusters with respect to some criteria such that each of them may belong to more than one cluster with different degrees of membership in order to solve it we first propose a new local search heuristic called fuzzy j means where the neighbourhood is defined by all possible centroid to pattern relocations the integer solution is then moved to a continuous one by an alternate step i e by finding centroids and membership degrees for all patterns and clusters to alleviate the difficulty of being stuck in local minima of poor value this local search is then embedded into the variable neighbourhood search metaheuristic results on five standard test problems from the literature are reported and compared with those obtained with the well known fuzzy c means heuristic it appears that solutions of substantially better quality are obtained with the proposed methods than with this former one

a marching cubes based failure surface propagation concept for three dimensional finite elements with non planar embedded strong discontinuities of higher order kinematics summary this paper presents an advanced failure surface propagation concept based on the marching cubes algorithm initially proposed in the field of computer graphics and applies it to the embedded finite element method when modeling three dimensional 3d solids at failure the propagation of the failure surface representing a crack or shear band should not exhibit a strong sensitivity to the details of the finite element discretization this results in the need for a propagation of the discrete failure zone through the individual finite elements which is possible for finite elements with embedded strong discontinuities whereas for two dimensional calculations the failure zone propagation location is easily predicted by the maximal principal stress direction more advanced strategies are needed to achieve a smooth failure surface in 3d simulations an example for such method is the global tracking algorithm which predicts the crack path by a scalar level set function computed on the basis of the solution of a simplified heat conduction like problem its prediction may though lead to various scenarios on how the failure surface may propagate through the individual finite elements in particular for a hexahedral eight node finite element 256 such cases exist to capture all those possibilities the marching cubes algorithm is combined with the global tracking algorithm and the finite elements with embedded strong discontinuities in this work in addition because many of the possible cases result in non planar failure surfaces within a single finite element and because the local quantities used to describe the kinematics of the embedded strong discontinuities are physically meaningful in a strict sense only for planar failure surfaces a remedy for such scenarios is proposed various 3d failure propagation simulations outline the performance of the proposed concept copyright 2013 john wiley sons ltd

a genetic learning process for the scaling factors granularity and contexts of the fuzzy rule based system data base abstract in this contribution we propose a new method to automatically learn the knowledge base of a fuzzy rule based system by finding an appropriate data base using a genetic algorithm and considering a simple generation method to derive the rule base our genetic process learns all the components of the data base number of labels working ranges and membership function shapes for each linguistic variable using a non linear scaling function to adapt the fuzzy partition contexts

a class of mixed assumed strain methods and the method of incompatible modes a three field mixed formulation in terms of displacements stresses and an enhanced strain field is presented which encompasses as a particular case the classical method of incompatible modes within this frame work incompatible elements arise as particular compatible mixed approximations of the enhanced strain field the conditions that the stress interpolation contain piece wise constant functions and be l2 ortho gonal to the enhanced strain interpolation ensure satisfaction of the patch test and allow the elimination of the stress field from the formulation the preceding conditions are formulated in a form particularly convenient for element design as an illustration of the methodology three new elements are developed and shown to exhibit good performance a plane 3d elastic plastic quad an axisymmetric element and a thick plate bending quad the formulation described herein is suitable for non linear analysis

learning the membership function contexts for mining fuzzy association rules by using genetic algorithms different studies have proposed methods for mining fuzzy association rules from quantitative data where the membership functions were assumed to be known in advance however it is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for mining fuzzy association rules this paper thus presents a new fuzzy data mining algorithm for extracting both fuzzy association rules and membership functions by means of a genetic learning of the membership functions and a basic method for mining fuzzy association rules it is based on the 2 tuples linguistic representation model allowing us to adjust the context associated to the linguistic term membership functions experimental results show the effectiveness of the framework