in this study, we offer a general view at the area of fuzzy modeling and fuzzymodels, identify the visible development phases and elaborate on a new and promisingdirections of system modeling by introducing a concept of granular models. granularmodels, especially granular fuzzy models constitute an important generalization of existingfuzzy models and, in contrast to the existing models, generat...

In this study, we offer a general view at the area of fuzzy modeling and fuzzymodels, identify the visible development phases and elaborate on a new and promisingdirections of system modeling by introducing a concept of granular models. Granularmodels, especially granular fuzzy models constitute an important generalization of existingfuzzy models and, in contrast to the existing models, generat...

Granular computing aims to develop a granular view for interpreting and solving problems. The model of neighborhood rough sets is one of effective tools for granular computing. This model can deal with complex tasks of classification learning. Despite the success of the neighborhood model in attribute reduction and rule learning, it still suffers from the issue of granularity selection. Namely,...

A framework is proposed for studying a particular class of set-theoretic approaches to granular computing. A granule is a subset of a universal set, a granular structure is a family of subsets of the universal set, and relationship between granules is given by the standard set-inclusion relation. By imposing different conditions on the family of subsets, we can define several types of granular ...

A theory of granular computing is presented. Some classical example are examined to obtain the hint of new directions Obvious examples are dynamic programming, fuzzy numbers, infinitesimal number and access control model, (pre)topological spaces are examined; Localized multi-level granulation can be modeled by generalized topological spaces, called neighborhood systems. For most general granula...

We discuss approximation spaces in the granular computing framework. Such approximation spaces generalise the approaches to concept approximation existing in rough set theory. Approximation spaces are constructed as higher level information granules and are obtained as the result of complex modelling. We present illustrative examples of modelling approximation spaces including approximation spa...

Recent advances in physically-based simulations have made it possible to generate realistic animations. However, in the case of solid-fluid coupling, wetting effects have rarely been noticed despite their visual importance especially in interactions between fluids and granular materials. This paper presents a simple particle-based method to model the physical mechanism of wetness propagating th...

Learning a distance metric from training samples is often a crucial step in machine learning and pattern recognition. Locality, compactness and consistency are considered as the key principles in distance metric learning. However, the existing metric learning methods just consider one or two of them. In this paper, we develop a multi-granularity distance learning technique. First, a new index, ...

A comparative study of the impact response of three-dimensional ordered granular sphere packings and continuum half-spaces made of elastic-perfectly plastic materials is conducted. Energy dissipation and plastic zone volume are characterized, and scaling laws with respect to material properties, size and loading variables are derived for both continuum and discrete (granular) systems. Due to st...

Suspensions of Blepharisma intermedium were fed latex particles for 5 min and then were separated from the particles by filtration. Samples were fixed at intervals after separation and incubated to demonstrate acid phosphatase activity. They were subsequently embedded and sectioned for electron microscopy. During formation of the food vacuole, the vacuolar membrane is acid phosphatase-negative....