Computational Geometry : Algorithms and Applications

Computational geometry emerged from the ?eld of algorithms design and analysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The success of the ?eld as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic information systems (GIS), robotics, and others--in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or dif?cult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simpli?ed many of the previous approaches. In this textbook we have tried to make these modern algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can also be used for self-study Publication of this book is a special event. This valuable title?lls a se- ous gap in domestic science and technical literature. At the same time it introduces a reader to the most recent achievements in the quickly dev- oping branch of knowledge which the computational intelligence has been for several years. The?eld, which is a subject of this book, is one of those important?elds of science which enable to process information included in data and give their reasonable interpretation programmed by a user. Recent decades have brought a stormy development of computer te- niquesandrelatedcomputationalmethods.Togetherwiththeirappearance and quick progress, theoretical and applied sciences developed as well, - ablingtheusertofullyutilizenewlycreatedcomputationalpotentialandto getknowledgeoutofincreasingwealthofdata.Thedevelopmentofcom- tational intelligence is then strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Without them the development of this?eld would be almost impossible, and its application practically marginal. That is why these techniques have especially developed in recent years. The development of computational intelligence systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. Nature when undertakes intelligent actions processes data in p- allel regulating and adjusting these actions through feedback mechanisms. This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots. The first part of the book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next various neural network architectures are presented and their learning algorithms are derived. Moreover, the family of evolutionary algorithms is discussed, in particular the classical genetic algorithm, evolutionary strategies and genetic programming, including connections between these techniques and neural networks and fuzzy systems. In the last part of the book, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared. This well-organized modern approach to methods and techniques of intelligent calculations includes examples and exercises in each chapter and a preface by Jacek Zurada, president of IEEE Computational Intelligence Society (2004-05).

this Book Focuses On Various Techniques Of Computational Intelligence, Both Single Ones And Those Which Form Hybrid Methods. Those Techniques Are Today Commonly Applied Issues Of Artificial Intelligence, E.g. To Process Speech And Natural Language, Build Expert Systems And Robots. The First Part Of The Book Presents Methods Of Knowledge Representation Using Different Techniques, Namely The Rough Sets, Type-1 Fuzzy Sets And Type-2 Fuzzy Sets. Next Various Neural Network Architectures Are Presented And Their Learning Algorithms Are Derived. Moreover, The Family Of Evolutionary Algorithms Is Discussed, In Particular The Classical Genetic Algorithm, Evolutionary Strategies And Genetic Programming, Including Connections Between These Techniques And Neural Networks And Fuzzy Systems. In The Last Part Of The Book, Various Methods Of Data Partitioning And Algorithms Of Automatic Data Clustering Are Given And New Neuro-fuzzy Architectures Are Studied And Compared.

Front Matter....Pages i-xii Computational Geometry....Pages 1-17 Line Segment Intersection....Pages 19-43 Polygon Triangulation....Pages 45-61 Linear Programming....Pages 63-93 Orthogonal Range Searching....Pages 95-120 Point Location....Pages 121-146 Voronoi Diagrams....Pages 147-171 Arrangements and Duality....Pages 173-190 Delaunay Triangulations....Pages 191-218 More Geometric Data Structures....Pages 219-241 Convex Hulls....Pages 243-258 Binary Space Partitions....Pages 259-281 Robot Motion Planning....Pages 283-306 Quadtrees....Pages 307-322 Visibility Graphs....Pages 323-333 Simplex Range Searching....Pages 335-355 Back Matter....Pages 357-386 Introduction Selected issues of artificial intelligence Methods of knowledge representation using rough sets Methods of knowledge representation using type-1 fuzzy sets Methods of knowledge representation using type-2 fuzzy sets Neural networks and their learning algorithms Evolutionary algorithms Data clustering methods Neuro-fuzzy systems of Mamdani, logical and Takagi-Sugeno type Flexible neuro-fuzzy systems.

This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.

Computational Geometry: Introduction Line Segment Intersection Polygon Triangulation Linear Programming Orthogonal Range Searching Point Location Voronoi Diagrams Arrangements and Duality Delaunay Triangulations More Geometric Data Structures Convex Hulls Binary Space Partitions Robot Motion Planning Quadtrees Visibility Graphs Simplex Range Searching Brand New International Paper-back Edition same as per description, **Economy edition, May have been printed in Asia with cover stating Not for sale in US. Legal to use despite any disclaimer on cover. Save Money. Contact us for any queries. Best Customer Support! All Orders shipped with Tracking Number.