In wireless mobile environments, we increasingly use data that depends on the location of mobile clients. However, requested geographical objects (GOs) do not exist in all areas with uniform distribution. More urbanized areas have greater population and greater GO density. Thus the results of queries may vary based on the perception of distance. We use urbanization as a criterion to analyze the...

This paper focuses on modelling fuzzy numbers with meaningful membership functions. More precisely, it proposes a method to construct trapezoidal fuzzy number approximations from raw discrete data. In many applications, input information is numerical, and therefore, particular fuzzy sets, such as fuzzy numbers, hold great interest and relevance in managing data imprecision and vagueness. The pr...

pulse echo b - scan imaging systems have been used for years in medical diagnosis. the theroy of such systems have been investigated by several researchers. in this paper, we introduce a new model for b - scan imaging system based on gaussian type transducer. an imaging system is normally identified by its point response function. this function describes the image of a single physical point obj...

The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaussian mixtures (GM) have been pointed out recently by Bezdek and Pal (1995). We extend this relation to their training, showing that learning rules by these models to estimate the cluster centers can be seen as approxim...

In this paper, the universal approximation property of one of the most frequently used type of fuzzy systems is proved. The type of fuzzy system in the present work employs triangle-shaped fuzzy membership functions (TSMF) for its input variables. The proof of the universal approximation property does not use the Stone-Weierstrass theorem because the TSMFs are not closed for the product; instea...

This tutorial presents the properties of the Gaussian probability density function. Subsequently, supervised and unsupervised pattern recognition methods are treated. Supervised classification algorithms are based on a labeled data set. The knowledge about the class membership of this training data set is used for the classification of new samples. Unsupervised learning methods establish cluste...

‎Radial basis functions (RBFs) are a powerful tool for approximating the solution of high-dimensional problems‎. ‎They are often referred to as a meshfree method and can be spectrally accurate‎. ‎In this paper, we analyze a new stable method for evaluating Gaussian radial basis function interpolants based on the eigenfunction expansion‎. ‎We develop our approach in two-dimensional spaces for so...

The intuitionistic linguistic set (ILS) is an extension of linguisitc variable. To overcome the drawback of using single real number to represent membership degree and non-membership degree for ILS, the concept of interval-valued intuitionistic linguistic set (IVILS) is introduced through representing the membership degree and non-membership degree with intervals for ILS in this paper. The oper...

Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In...