This book is about Granular Computing (GC) - an emerging conceptual and of information processing. As the name suggests, GC concerns computing paradigm processing of complex information entities - information granules. In essence, information granules arise in the process of abstraction of data and derivation of knowledge from information. Information granules are everywhere. We commonly use granules of time (seconds, months, years). We granulate images; millions of pixels manipulated individually by computers appear to us as granules representing physical objects. In natural language, we operate on the basis of word-granules that become crucial entities used to realize interaction and communication between humans. Intuitively, we sense that information granules are at the heart of all our perceptual activities. In the past, several formal frameworks and tools, geared for processing specific information granules, have been proposed. Interval analysis, rough sets, fuzzy sets have all played important role in knowledge representation and processing. Subsequently, information granulation and information granules arose in numerous application domains. Well-known ideas of rule-based systems dwell inherently on information granules. Qualitative modeling, being one of the leading threads of AI, operates on a level of information granules. Multi-tier architectures and hierarchical systems (such as those encountered in control engineering), planning and scheduling systems all exploit information granularity. We also utilize information granules when it comes to functionality granulation, reusability of information and efficient ways of developing underlying information infrastructures.
Granular Computing is an emerging conceptual and computing paradigm of information processing. It has been motivated by the urgent need for intelligent processing of empirical data that is now commonly available in vast quantities, into a humanly manageable abstract knowledge. In this sense, granular computing offers a landmark change from the current machine-centric to human-centric approach to information and knowledge. The theoretical foundations of granular computing are exceptionally sound and involve set theory (interval mathematics), fuzzy sets, rough sets, and random sets linked together in a highly comprehensive treatment of this emerging paradigm."Granular Computing: An Introduction" covers a full spectrum of granular computing from the basic methodology through algorithms and granular worlds, to a representative spectrum of applications. This book will appeal to all developing intelligent systems either working at the methodological level or interested in detailed system realizations. The reader is provided with the underlying material on granular computing, as well as exposed to the current developments where it finds the most visible applications.
Furthermore, this book provides an extensive bibliography after each chapter - an indispensable source of information to anyone seriously pursuing research in this rapidly developing area. "Granular Computing: An Introduction" is designed to meet the needs of a professional audience composed of researchers and practitioners in industry and graduate level students in computer science and engineering.
