Not all approximations arise from information systems. The problem of fitting approximations, subjected to some rules (and related data), to information systems in a rough scheme of things is known as the inverse problem. The inverse problem is more general than the duality (or abstract representation) problems and was introduced by the present author in her earlier papers. From the practical p...

This paper considers dissimilarity measures and clustering techniques for two special cases of set-defined objects: fuzzy granules and subsequence time series. To deal with clustering of such kind of objects, we propose two implementations that generalize the Fuzzy C-Means algorithm to granular feature spaces. Granular computing is a paradigm oriented towards capturing and processing meaningful...

This work presents the general idea of granular description of temporal signal, particularly biomedical signal sampled with constant frequency. The main idea of presented method is based on using triangular fuzzy numbers as information granules in temporal and amplitude spaces. The amplitude space contains values of first few derivatives of underlying signal. The construction of data granules i...

Minkowski operators (dilation and erosion of sets in vector spaces) have been extensively used in computer graphics, image processing to analyze the structure of materials, and more recently in molecular dynamics. Here, we apply those mathematical concepts to extend the discrete element method to simulate granular materials with complex-shaped particles. The Voronoi-Minkowski diagrams are intro...

Granular computing has been applied in many fields to solve problems and describe many spaces at different granularity and hierarchies. This paper proposes a rule generation approach based on granular computing in the frame of rough mereology. The proposed approaches generates a single rule granule from granular space in each step instead of selecting a suitable attribute according to some meas...

In this paper, we propose an incremental method of Granular Networks (GN) to construct conceptual and computational platform of Granular Computing (GrC). The essence of this network is to describe the associations between information granules including fuzzy sets formed both in the input and output spaces. The context within which such relationships are being formed is established by the system...

We develop two algebraic semantics for bitten rough set theory ([19]) over similarity spaces and their abstract granular versions. Connections with choice based generalized rough semantics developed in [15] by the present author and general cover based rough set theories are also considered.

The automation of bioregenerative life support systems poses challenges for the development of model-based approaches given the varying characteristic of the biological processes that constitute them. Switching control paradigms offer an alternative for the management of such uncertainty by introducing flexibility into the control path and allowing for different control modes depending on the o...