Transactions on Rough Sets XV [electronic resource] / edited by James F. Peters, Andrzej Skowron.
Tipo de material:
TextoSeries Lecture Notes in Computer Science, 7255Editor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Descripción: IX, 181p. 54 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642319037Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Electronic data processing | Information storage and retrieval systems | Artificial intelligence | Computer vision | Optical pattern recognition | Computer Science | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Mathematical Logic and Formal Languages | Numeric Computing | Image Processing and Computer Vision | Information Storage and RetrievalFormatos físicos adicionales: Sin títuloClasificación CDD: 006.4 Clasificación LoC:Q337.5TK7882.P3Recursos en línea: de clik aquí para ver el libro electrónico Springer eBooksResumen: 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 XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning; the introduction of multi-valued near set theory; the advent of a complete system that supports a rough-near set approach to digital image analysis; and an exhaustive study of the mathematics of vagueness.
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 XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning; the introduction of multi-valued near set theory; the advent of a complete system that supports a rough-near set approach to digital image analysis; and an exhaustive study of the mathematics of vagueness.
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