Spatial Evolutionary Modeling (Spatial Information Systems)

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Spatial Evolutionary Modeling (Spatial Information Systems) Overview

Evolutionary models (e.g., genetic algorithms, artificial life), explored in other fields for the past two decades, are now emerging as an important new tool in GIS for a number of reasons. First, they are highly appropriate for modeling geographic phenomena. Secondly, geographical problems are often spatially separate (broken down into local or regional problems) and evolutionary algorithms can exploit this structure. Finally, the ability to store, manipulate, and visualize spatial data has increased to the point that space-time-attribute databases can be easily handled.

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Spatial Coherence for Visual Motion Analysis: First International Workshop, SCVMA 2004, Prague, Czech Republic, May 15, 2004, Revised Papers (Lecture ... Vision, Pattern Recognition, and Graphics)

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Spatial Coherence for Visual Motion Analysis: First International Workshop, SCVMA 2004, Prague, Czech Republic, May 15, 2004, Revised Papers (Lecture ... Vision, Pattern Recognition, and Graphics) Overview

This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Spatial Coherence for Visual Motion Analysis, 2004, held in May 2004. The eleven revised full research papers presented went through two rounds of reviewing and improvement. The papers in this volume cover a wide range in the field of motion analysis that is a central problem in computer vision. The workshop examined techniques for integrating spatial coherence constraints during motion analysis of image sequences.

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Qualitative Representation of Spatial Knowledge (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)

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Qualitative Representation of Spatial Knowledge (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) Overview

This book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved.
The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems.

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Beyond the Map: Archaeology and Spatial Technologies (Nato a S I Series Series a, Life Sciences)

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Beyond the Map: Archaeology and Spatial Technologies (Nato a S I Series Series a, Life Sciences) Overview

This set of papers by European and North American archaeologists explore the interface between new spatial technologies and areas of theoretical concern in spatial archaeology. Differing aspects of landscape, such as vision, perception and movement, are explored through a series of case studies that focus on how spatial technologies can influence archaeological interpretation and to what extent these new technologies can be manipulated to take us beyond 2-dimensional maps. Individual site-based analyses and new applications of predictive modelling are also presented and assessed together with the wider questions of spatial technologies within heritage management.

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Spatial Analytical (Gisdata Series , Vol 4)

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Spatial Analytical (Gisdata Series , Vol 4) Overview

This text presents the latest information on incorporating spatial analysis tools into GIS, and includes concepts and applications from both the environmental and socio- economic sciences.

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Multivariate Nonparametric Methods with R: An approach based on spatial signs and ranks (Lecture Notes in Statistics)

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Multivariate Nonparametric Methods with R: An approach based on spatial signs and ranks (Lecture Notes in Statistics) Overview

This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory.

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