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Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference.
"This book documents the most relevant contributions to the introduction of networked, dynamic, agile, and virtual organizational models; definitions; taxonomies; opportunities; and reference models and architectures. It creates a repository of the main developments regarding the virtual organization, compiling definitions, characteristics, comparisons, advantages, practices, enabling technologies, and best practices"--Provided by publisher.
This book constitutes the refereed proceedings of the 16th International Conference on Artificial Reality and Telexistence, ICAT 2006, held in Hangzhou, China in November/December 2006. The 138 revised papers cover anthropomorphic intelligent robotics, artificial life, augmented reality, distributed and collaborative VR system, motion tracking, real time computer simulation virtual reality, as well as VR interaction and navigation techniques.
Annotation The book presents state-of-the-art knowledge about decision-making support systems (DMSS). Its main goals are to provide a compendium of quality chapters on decision-making support systems that help diffuse scarce knowledge about effective methods and strategies for successfully designing, developing, implementing, and evaluating decision-making support systems, and to create an awareness among readers about the relevance of decision-making support systems in the current complex and dynamic management environment.
The proper management of geographic data can provide assistance to a number of different sectors within society. As such, it is imperative to continue advancing research for spatial data analysis. The Handbook of Research on Geographic Information Systems Applications and Advancements presents a thorough overview of the latest developments in effective management techniques for collecting, processing, analyzing, and utilizing geographical data and information. Highlighting theoretical frameworks and relevant applications, this book is an ideal reference source for researchers, academics, professionals, and students actively involved in the field of geographic information systems.
The book describes a novel ideology and supporting information technology for integral management of both civil and defence-orientated large, distributed dynamic systems. The approach is based on a high-level Spatial Grasp Language, SGL, expressing solutions in physical, virtual, executive and combined environments in the form of active self-evolving and self-propagating patterns spatially matching the systems to be created, modified and controlled. The communicating interpreters of SGL can be installed in key system points, which may be in large numbers (up to millions and billions) and represent equipped humans, robots, laptops, smartphones, smart sensors, etc. Operating under gestalt-inspired scenarios in SGL initially injected from any points, these systems can be effectively converted into goal-driven spatial machines (rather than computers as dealing with physical matter too) capable of responding to numerous challenges caused by growing world dynamics in the 21st century. Including numerous practical examples, the book is a valuable resource for system managers and programmers.
CCIS 107 is the second volume of the proceedings of the Fifth International Symposium on Intelligence Computation and Applications (ISICA 2010)held in Wuhan, China, October 22–24, 2010. Thirty-one papers among 267 submissions were selected and included in CCIS 107. This volume features the most up-to-date research in evolutionary design, evolutionary optimization, hybrid evolutionary algorithms, intelligent systems, particle swarm optimization, and predictive modeling. CCIS 107 is dedicated to the memory of Lishan Kang. ISICA conferences were one of the ?rst series of international conferences on computational - telligence that combined elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to arti?cial intelligence. The idea for ISICA came about after Lishan Kang organized an international s- posium on evolutionarycomputation at Wuhan University in 2000. After he was invited to be the Director of the School of Computer Science, China University of Geosciences, he wondered whether he could establish such discussion forums on computational intelligence at China University of Geosciences. With support from his university, the School of Computer Science organizedthe ?rst ISICA in 2005, in which some of the leading ?gures from the scienti?c computing world were invited, including H. -P. Schwefel, Germany, M. Schoenauer, France, D. J. Evans, UK, T. Higuchi, Japan, Z. Michalewicz, Australia, and X. Yao, UK. The Second ISICA was jointly held in 2007 with the 7th International C- ference on Evolvable Systems: From Biology to Hardware (ICES 2007).