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q-Rung Orthopair Fuzzy Sets - - Bog - Springer Verlag, Singapore - Plusbog.dk

q-Rung Orthopair Fuzzy Sets - - Bog - Springer Verlag, Singapore - Plusbog.dk

Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications - Xinwang Liu - Bog - Springer Verlag, Singapore - Plusbog.dk

Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications - Xinwang Liu - Bog - Springer Verlag, Singapore - Plusbog.dk

Wavelet Analysis on Local Fields of Positive Characteristic - Biswaranjan Behera - Bog - Springer Verlag, Singapore - Plusbog.dk

Synergies in Analysis, Discrete Mathematics, Soft Computing and Modelling - - Bog - Springer Verlag, Singapore - Plusbog.dk

Analytic Continuation and q-Convexity - Takeo Ohsawa - Bog - Springer Verlag, Singapore - Plusbog.dk

Analytic Continuation and q-Convexity - Takeo Ohsawa - Bog - Springer Verlag, Singapore - Plusbog.dk

The focus of this book is on the further development of the classical achievements in analysis of several complex variables, the analytic continuation and the analytic structure of sets, to settings in which the q- pseudoconvexity in the sense of Rothstein and the q- convexity in the sense of Grauert play a crucial role. After giving a brief survey of notions of generalized convexity and their most important results, the authors present recent statements on analytic continuation related to them. Rothstein (1955) first introduced q- pseudoconvexity using generalized Hartogs figures. Słodkowski (1986) defined q- pseudoconvex sets by means of the existence of exhaustion functions which are q- plurisubharmonic in the sense of Hunt and Murray (1978). Examples of q- pseudoconvex sets appear as complements of analytic sets. Here, the relation of the analytic structure of graphs of continuous surfaces whose complements are q- pseudoconvex is investigated. As an outcome, the authors generalize results by Hartogs (1909), Shcherbina (1993), and Chirka (2001) on the existence of foliations of pseudoconcave continuous real hypersurfaces by smooth complex ones. A similar generalization is obtained by a completely different approach using L²-methods in the setting of q- convex spaces. The notion of q- convexity was developed by Rothstein (1955) and Grauert (1959) and extended to q- convex spaces by Andreotti and Grauert (1962). Andreotti-Grauert''s finiteness theorem was applied by Andreotti and Norguet (1966-1971) to extend Grauert''s solution of the Levi problem to q- convex spaces. A consequence is that the sets of ( q- 1)-cycles of q- convex domains with smooth boundaries in projective algebraic manifolds, which are equipped with complex structures as open subsets of Chow varieties, are in fact holomorphically convex. Complements of analytic curves are studied, and the relation of q- convexity and cycle spaces is explained. Finally, results for q- convex domains in projective spaces are shown and the q- convexity in analytic families is investigated.

DKK 468.00
1

Aviation System Risks and Safety - Kuklev E.a. - Bog - Springer Verlag, Singapore - Plusbog.dk

Concepts of Soft Computing - Nisha Rani Mahato - Bog - Springer Verlag, Singapore - Plusbog.dk

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications - Muhammad Summair Raza - Bog - Springer Verlag,

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications - Muhammad Summair Raza - Bog - Springer Verlag,

This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms. The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.

DKK 731.00
1

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications - Muhammad Summair Raza - Bog - Springer Verlag,

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications - Muhammad Summair Raza - Bog - Springer Verlag,

This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms. The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.

DKK 986.00
1

Lithium Ion Glassy Electrolytes - - Bog - Springer Verlag, Singapore - Plusbog.dk

History of Economic Ideas in 20 Talks - Cheng Chung Lai - Bog - Springer Verlag, Singapore - Plusbog.dk

Socialism with Chinese Characteristics - Roland Boer - Bog - Springer Verlag, Singapore - Plusbog.dk

Groups and Symmetry - Bijan Davvaz - Bog - Springer Verlag, Singapore - Plusbog.dk

Redefining Chinese Literature and Art - Jixi Yuan - Bog - Springer Verlag, Singapore - Plusbog.dk

Housing Reform and China’s Real Estate Industry - Guangchun Gao - Bog - Springer Verlag, Singapore - Plusbog.dk

Advances in Fault Detection and Diagnosis Using Filtering Analysis - Ziyun Wang - Bog - Springer Verlag, Singapore - Plusbog.dk