advances spatial reasoning (17 risultati)

Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Edition 1990. Editeur différent. Tome 2. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1990. Different publisher. Volume 2. Ammareal gives back up to 15% of this item's net price to charity organizations.

Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Salissures sur la tranche. Couverture différente. Edition 1990. Tome 1. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Stains on the edge. Different cover. Edition 1990. Volume 1. Ammareal gives back up to 15% of this item's net price to charity organizations.

Hardcover. Condizione: Très bon. Ancien livre de bibliothèque. Edition 1990. Editeur différent. Tome 1. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1990. Different publisher. Volume 1. Ammareal gives back up to 15% of this item's net price to charity organizations.

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Condizione: Neu. Generating Relation Algebras for Qualitative Spatial Reasoning | Advances in Artificial Intelligence | Prathap Siddavaatam | Taschenbuch | 84 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846591260 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Condizione: New.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 596 | Sprache: Englisch | Produktart: Bücher | Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises.The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.

Condizione: New.

Taschenbuch. Condizione: Neu. Visual and Spatial Analysis | Advances in Data Mining, Reasoning, and Problem Solving | James Schwing (u. a.) | Taschenbuch | xx | Englisch | 2010 | Springer Netherland | EAN 9789048167500 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In.

Condizione: As New. Unread book in perfect condition.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain- combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises.The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain- combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises.The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.

Hardcover. Condizione: Brand New. 1st edition. 576 pages. 9.50x6.50x1.25 inches. In Stock.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - First-order logic is symbolized reasoning in which each sentence, or statement, is broken down into a subject and a predicate. The predicate modifies or defines the properties of the subject. Apart from the formal properties, qualitative spatial representation and reasoning is an important criterion for choosing a set of spatial relations that humans perceive and choose the same relations for distinguishing spatial configurations. Since its earliest inception many theories have been proposed for mereotopology in AI among which Region Connection Calculus (RCC) is most prominent. RCC provides an axiomatization of space which takes regions as primitive, rather than as constructions from sets of points. The expressiveness of the RCC in relational logic is far greater than the original 8 RCC base relations might suggest. In my thesis I contemplated ways to automatically generate representable relational algebras using spatial data based on RCC. Contrary to physical theories about space and time, my research based on mereotopological calculi permits rather inexpensive reasoning about entities located in space and time. For e.g. usage in handling spatial GIS queries and robot navigation.