Developing methods for approximation of compound concepts expressing the result of perception belongs to the main challenges of Perception Based Computing (PBC) [70]. The perceived concepts are expressed in natural language. We discuss the rough-granular approach to approximation of such concepts from sensory data and domain knowledge. This additional knowledge, represented by ontology of conce...

With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are coming for knowledge discovery and data mining modeling problems. In this dissertation work, a framework named Granular Support Vector Machines (GSVM) is proposed to systematically and formally combine statistical learning theory, granular computing theory and soft computing theory to address challeng...

This issue introduces the state-of-art in granular soft computng for pattern recognition and mining and presents some novel ontributions. Granulation is a computing paradigm, among othrs such as self-reproduction, self-organization, functioning of rain, Darwinian evolution, group behavior, cell membranes, and orphogenesis that are abstracted from natural phenomena. Granlation is inherent in hum...

Granular computing, based on rough set theory [1, 2], provides the basis for a new computing paradigm [3, 4]. Applying granular computing to logical reasoning processes, we have proposed granular reasoning for connecting possible world semantics and granular computing [5], and developed a granular reasoning framework called a zooming reasoning system [6–8]. The key concept of zooming reasoning ...

What is granular computing? As we have said in [6]: There are no mathematically valid formal definitions yet. Informally, any computing theory/technology that involves elements and granules (generalized subsets) may be called granular computing (GrC). Intuitively, elements are the data, and granules are the basic knowledge. So granular computing includes data and knowledge computing/engineering...

Granular computing is an emerging field of research that attempts to formalize and explore methods and heuristics for human problem solving with multiple levels of granularity and abstraction. A fundamental issue of granular computing is the construction, representation and utilization of granules and granular structures. Basic granules represent the basic pieces of knowledge. A granular struct...

Granular computing(GrC) is a recent label, roughly speaking, jointly coined by Lin and Zadeh in 1996 to denote an emgering technolgy that is based on the computing/mathematical theory of an ancient concept of granulation. In this paper, we present the ”final” GrC model that simplify the earlier version.

In this paper, we argue that granular computing may have many potential applications in knowledge discovery and data mining. Three related basic operations of granular computing are examined: granulation of the universe, characterization of granules, and relationships between granules. Their connections to the tasks of knowledge discovery and data mining are analyzed.

This article is bout the data analysis and mining aspects of Granular Computing(GrC) and Rough Set Theory(RST). This subject involves four concepts, deductive data analysis and mining (DDAM), relational databases (RDB), rough set theory (RST) and granular computing(GrC). The results are quite far reaching.