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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.This fifth volume of the Transactions on Rough Sets is dedicated to the monumental life, work and creative genius of Zdzis{l}aw Pawlak, the originator of rough sets, who passed away in April 2006. It opens with a commemorative article that gives a brief coverage of Pawlak's works in rough set theory, molecular computing, philosophy, painting and poetry. Fifteen papers explore the theory of rough sets in various domains as well as new applications of rough sets. In addition, this volume of the TRS includes a complete monograph on rough sets and approximate Boolean reasoning systems that includes both the foundations as well as applications of data mining.
VolumeVIIIoftheTransactions on Rough Sets (TRS)containsa widespectrum of contributions to the theory and applications of rough sets. The pioneering work by Prof. Zdzis law Pawlak led to the introduction of knowledge representation systems during the early 1970s and the discovery of rough sets during the early 1980s. During his lifetime, he nurtured worldwide interest in approximation, approximate reasoning, and rough set theory and its 1 applications . Evidence of the in?uence of Prof. Pawlak’s work can be seen in the growth in the rough-set literature that now includes over 4000 publications 2 by more than 1900 authors in the rough set database as well as the growth and 3 maturity of the International Rough Set Society . This volume of TRS presents papers that introduce a number of new - vances in the foundations and applications of arti?cial intelligence, engineering, logic, mathematics, and science. These advances have signi?cant implications in a number of researchareas.In addition, it is evident from the papers included in this volume that roughset theoryand its application forma veryactiveresearch area worldwide. A total of 58 researchers from 11 countries are represented in this volume, namely, Australia, Canada, Chile, Germany, India, Poland, P.R. China, Oman, Spain, Sweden, and the USA. Evidence of the vigor,breadth, and depth of research in the theory and applications rough sets can be found in the articles in this volume. This volume contains 17 papers that explore a number of research streams.
Volume XI of the Transactions on Rough Sets (TRS) provides evidence of f- ther growth in the rough set landscape, both in terms of its foundations and applications. This volume provides further evidence of the number of research streams that were either directly or indirectly initiated by the seminal work on rough 1 sets by Zdzis law Pawlak (1926-2006) . Evidence of the growth of various rough 2 set-based research streams can be found in the rough set database . Thisvolumecontainsarticlesintroducingadvancesinthefoundationsand- plicationsofroughsets.These advancesinclude: calculusofattribute-value pairs useful in mining numerical data, de?nability and coalescence of approximations, variable consistency generalization approach to bagging controlled by measures of consistency, classical and dominance-based rough sets in the search for genes, judgementaboutsatis?abilityunderincompleteinformation,irreducibledescr- tive sets of attributes for information systems useful in the design of concurrent data models, computational theory of perceptions (CTP) and its characteristics and the relation with fuzzy-granulation, methods and algorithms of the Net- TRS system, a recursive version of the apriori algorithm designed for parallel processing, and decision table reduction method based on fuzzy rough sets. Theeditorsandauthorsofthisvolumeextendtheirgratitudetothereviewers of articles in this volume, Alfred Hofmann, Ursula Barth, Christine Reiss and the LNCS sta? at Springer for their support in making this volume of the TRS possible.
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XIII contains 14 papers which introduce a number of new advances in both the foundations and the applications of rough sets. These are mathematical structures of generalized rough sets in infinite universes, approximations of arbitrary binary relations, and attribute reduction in decision-theoretic rough sets. Methodological advances introduce rough set-based and hybrid methodologies for learning theory, attribution reduction, decision analysis, risk assessment, and data mining tasks such as classification and clustering. In addition, this volume contains regular articles on mining temporal software metrics data, C-GAME discretization method, perceptual tolerance intersection as an example of a near set operation and compression of spatial data with quadtree structures.
This volume of the Transactions on Rough Sets commemorates the life and work of Zdzislaw Pawlak (1926-2006), whose legacy is rich and varied. It presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak, introducing a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science.
This volume contains revised papers from the Rough Set and Knowledge Technology Conference (RSKT 2008), together with five papers introducing advances in rough set theory and its applications. It is part of the LNCS Transactions on Rough Sets series.
This two-volume set LNAI 10313 and LNAI 10314 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2017, held in Olsztyn, Poland, in July 2017. The 74 revised full papers presented together with 16 short papers and 16 invited talks, were carefully reviewed and selected from 130 submissions. The papers in this two set-volume of IJCRS 2017 follow the track already rutted by RSCTC and JRS conferences which aimed at unification of many facets of rough set theory from theoretical aspects of the rough set idea bordering on theory of concepts and going through algebraic structures, topological structures, logics for uncertain reasoning, decision algorithms, relations to other theories of vagueness and ambiguity, then to extensions of the rough set idea like granular structures, rough mereology, and to applications of the idea in diverse fields of applied science including hybrid methods like rough-fuzzy, neuro-rough, neuro-rough-fuzzy computing. IJCRS 2017 encompasses topics spread among four main tracks: Rough Sets and Data Science (in relation to RSCTC series organized since 1998); Rough Sets and Granular Computing (in relation to RSFDGrC series organized since 1999); Rough Sets and Knowledge Technology (in relation to RSKT series organized since 2006); and Rough Sets and Intelligent Systems (in relation to RSEISP series organized since 2007).
The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.
Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.
This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being. This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches. We are proud to offer the readers this book.