Intelligent Spatial Decision Support Systems
Published on 22. September 2011
Book
Paperback/Softback
XV, 470 pages
978-3-642-64521-1 (ISBN)
Description
In the past half century, we have experienced two major waves of methodological development in the study of human behavior in space and time. The fIrst wave was the well known "quantitative revolution" which propelled geography from a mainly descriptive discipline to a scientifIc discipline using formalism such as probability, statistics, and a large-number of mathematical methods for analyzing spatial structures and processes under certainty and uncertainty. The second wave is the recent advancement of geographical information systems which equips geographers with automation in the storage, retrieval, analysis, and display of data. Both developments have significant impacts on geographical studies in general and solutions to real life spatio-temporal problems in particular. They have found applications in urban and regional planning, automated mapping and facilities management, transportation planning and management, as well as environmental planning and management, to name but a few examples. Both developments have one thing in common. They one way or the other use computer to process and analyze data. However, not until recently, there has been very little interaction between the two. Quantitative models have largely been developed independent of the underlying data models and structures representing the spatial phenomena or processes under study. Display of analysis results has been primitive in terms of the utilization of computer graphic technologies. Formal models, in addition to their technical difficulties, have poor capability in communication with users. Geographical information systems, on the other hand, have originally been developed with a slight intention to entertain powerful analytical models.
More details
Series
Edition
Softcover reprint of the original 1st ed. 1997
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XV, 470 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 27 mm
Weight
739 gr
ISBN-13
978-3-642-64521-1 (9783642645211)
DOI
10.1007/978-3-642-60714-1
Schweitzer Classification
Other editions
Additional editions
Book
05/1997
Springer
€85.55
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Person
Yee Leung is Emeritus Professor of the Department of Geography and Resource Management and Honorary Senior Research Fellow of the Institute of Space and Earth Information Science at the Chinese University of Hong Kong, Hong Kong SAR, P. R. China. He is Pioneer of the theory and applications of fuzzy sets approach to geographical research and has done novel research on uncertainty analysis in geographical modeling and spatial information involving probability, statistics, fuzzy set, rough set, and granular computing. His research also covers artificial intelligence in general and machine learning including deep learning, neural network, evolutionary computation, and optimization in particular. He has published six monographs and more than 200 articles in reputed international journals and book chapters mainly in geography, geographical information science, artificial intelligence, computer science, and information science. His research is holistically reflected in the landmark research monographs.
Content
1 Introduction.- 1.1 On Complexity of Spatial Decision Making.- 1.2 Basic Notions of Spatial Decision Support Systems.- 1.3 A General Architecture for Intelligent Spatial Decision Support Systems.- 1.4 Purpose and Structure of the Monograph.- 2 Symbolic Approaches to Spatial Knowledge Representation and Inference.- 2.1 A Note on Knowledge Representation and Inference.- 2.2 Propositional and Predicate Logic.- 2.3 Production Systems.- 2.4 Semantic Networks.- 2.5 Frames.- 2.6 Object-Oriented Approach.- 2.7 A Note on Hybrid Representations.- 3 Fuzzy Logic Approaches to Spatial Knowledge Representation and Inference.- 3.1 A Note on Fuzzy Logic.- 3.2 Fuzzy Propositions.- 3.3 Fuzzy IF-THEN Propositions and their Translations.- 3.4 Fuzzy Inference.- 3.5 Linguistic Approximation in Fuzzy Inference.- 3.6 Fuzzy Rule-Based Inference Requiring Precise Output.- 4 Management of Uncertainty in Knowledge Representation and Inference.- 4.1 On Measures of Confidence.- 4.2 Probabilistic Approaches.- 4.3 Certainty Factor.- 4.4 Shafer-Dempster's Belief Functions.- 4.5 Possibility-Necessity Approach.- 4.6 A Note on the Theory of Inclusion.- 5 Neural Network Approaches to Spatial Knowledge Representation and Inference.- 5.1 A Remark on Symbolic and Neural Network Approaches to Knowledge Representation and Inference.- 5.2 A Brief Review of Neural Networks Research.- 5.3 Spatial Knowledge Representation and Inference by Feedforward Neural Networks.- 5.4 Spatial Knowledge Representation and Inference by Recurrent Neural Networks.- 5.5 A Note on Hybrid Spatial Decision Support Systems.- 6 Knowledge Acquisition for Spatial Inference - The Case of Genetic Algorithms.- 6.1 The Necessity of Automatic Knowledge Acquisition.- 6.2 A Brief Note on Genetic Algorithms.- 6.3 A Formalism of CanonicalGenetic Algorithms.- 6.4 Rule Learning Using Genetic Algorithms.- 6.5 Evolving Neural Networks Using Genetic Algorithms.- 6.6 A Remark on Genetic Algorithms.- 7 Spatial Data Models and Data Structures.- 7.1 A Note on Data Models and Data Structures.- 7.2 Spatial Data Models and Data Structures within the Layer-Viewed Framework.- 7.3 Relational Database for Precise Data.- 7.4 Fuzzy Relational Model and Database.- 7.5 Issues of Spatial Database Accuracy.- 7.6 Spatial Data Models and Data Structures within the Object-Viewed Framework.- 8 Management of Models in Spatial Decision Support Systems.- 8.1 The Necessity of a Systematic Management of Models in Spatial Decision Support Systems.- 8.2 Model Classification and Organization.- 8.3 Model-Data Linkage - Spatial Network Analysis as a Case Study.- 9 An Expert System Shell for Building Spatial-Decision- Support-System Development Tool.- 9.1 On the Architecture of a Spatial-Decision-Support-System Development Tool.- 9.2 The Fuzzy-Logic-Based Expert System Shell (FLESS) - The Nerve Center of the Spatial-Decision-Support-System Development Tool.- 9.3 Equipping FLESS with Automatic Knowledge-Acquisition Capabilities.- 9.4 Application of FLESS in Building Expert Systems for Spatial Classification Problems.- 10 A Spatial Decision Support System for Flood Simulation and Damage Assessment Using FLESS.- 10.1 History of Flooding in Sun Hugou Watershed.- 10.2 Overall Design of the Flood Simulation and Damage Assessment Process.- 10.3 The Flood Simulation and Damage Assessment Decision Support System.- 11 An Object-Oriented Expert System Shell for Building Spatial Decision Support Systems.- 11.1 A Note on Object-Oriented Approach to Integrative Spatial Decision Support Systems.- 11.2 The Architecture of an Object-Oriented ExpertSystem Shell for Spatial Inference.- 11.3 An Expert System for Solving Hierarchical Programming Problems.- 11.4 A Pedagogic Example.- 12 Conclusion.- 12.1 Summary.- 12.2 Outlook and Research Directions.- References.- List of Figures.- List of Tables.