Intelligent Spatial Decision Support Systems

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.

Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.

Although interest in Spatial Decision Support Systems (SDSS) continues to grow rapidly in a wide range of disciplines, students, planners, managers, and the research community have lacked a book that covers the fundamentals of SDSS along with the advanced design concepts required for building SDSS. Filling this need, Spatial Decision Support Systems: Principles and Practices provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. It integrates research from a variety of disciplines, including the geosciences, to supply a complete overview of SDSS technologies and their application from an interdisciplinary perspective. This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools. The book consists of four major parts, each addressing different topic areas in SDSS: Presents an introduction to SDSS and the evolution of SDSS Covers the essential and optional components of SDSS Focuses on the design and implementation of SDSS Reviews SDSS applications from various domains and disciplines—investigating current challenges and future directions The text includes numerous detailed case studies, example applications, and methods for tailoring SDSS to your work environment. It also integrates sample code segments throughout. Addressing the technical and organizational challenges that affect the success or failure of SDSS, the book concludes by considering future directions of this rapidly emerging field of study.

Since the late 1980s, a large number of very user-friendly tools for fuzzy control, fuzzy expert systems, and fuzzy data analysis have emerged. This has changed the character of this area and started the area of `fuzzy technology'. The next large step in the development occurred in 1992 when almost independently in Europe, Japan and the USA, the three areas of fuzzy technology, artificial neural nets and genetic algorithms joined forces under the title of `computational intelligence' or `soft computing'. The synergies which were possible between these three areas have been exploited very successfully. Practical Applications of Fuzzy Sets focuses on model and real applications of fuzzy sets, and is structured into four major parts: engineering and natural sciences; medicine; management; and behavioral, cognitive and social sciences. This book will be useful for practitioners of fuzzy technology, scientists and students who are looking for applications of their models and methods, for topics of their theses, and even for venture capitalists who look for attractive possibilities for investments.

"This book focuses on the latest innovations in the process of manufacturing in engineering"--Provided by publisher.

Several emerging phenomena and technologies, such as the increasing availability of open source software and the continuing evolution of distributed computing, are introducing a new dynamic into information system development. Emerging Spatial Information Systems and Applications presents innovative spatial information systems that have been developed for a specific problem or decision-making situation and discusses key concepts and theories underlying current spatial information systems, as well as technology trends and emerging concepts that may impact spatial information system development and applications.

This book provides an extensive review of three interrelated issues: land fragmentation, land consolidation, and land reallocation, and it presents in detail the theoretical background, design, development and application of a prototype integrated planning and decision support system for land consolidation. The system integrates geographic information systems (GIS) and artificial intelligence techniques including expert systems (ES) and genetic algorithms (GAs) with multi-criteria decision methods (MCDM), both multi-attribute (MADM) and multi-objective (MODM). The system is based on four modules for measuring land fragmentation; automatically generating alternative land redistribution plans; evaluating those plans; and automatically designing the land partitioning plan. The presented research provides a new scientific framework for land-consolidation planning both in terms of theory and practice, by presenting new findings and by developing better tools and methods embedded in an integrated GIS environment. It also makes a valuable contribution to the fields of GIS and spatial planning, as it provides new methods and ideas that could be applied to improve the former for the benefit of the latter in the context of planning support systems. “From the 1960s, ambitious research activities set out to observe regarding IT-support of the complex and time consuming redistribution processes within land consolidation – without any practically relevant results, until now. This scientific work is likely to close that gap. This distinguished publication is highly recommended to land consolidation planning experts, researchers and academics alike.” – Prof. Dr.-Ing. Joachim Thomas, Münster/ Germany "Planning support systems take new scientific tools based on GIS, optimisation and simulation and use these to inform the process of plan-making and policy. This book is one of the first to show how this can be consistently done and it is a triumph of demonstrating how such systems can be made operational. Essential reading for planners, analysts and GI scientists." – Prof. Michael Batty, University College London

This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.