Scalable Uncertainty Management
Scalable Uncertainty Management

Author: Salem Benferhat

Publisher: Springer

Published: 2011-10-07

Total Pages: 574

ISBN-13: 3642239633

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This book constitutes the refereed proceedings of the 5th International Conference on Scalable Uncertainty Management, SUM 2011, held in Dayton, OH, USA, in October 2011. The 32 revised full papers and 3 revised short papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on argumentation systems, probabilistic inference, dynamic of beliefs, information retrieval and databases, ontologies, possibility theory and classification, logic programming, and applications.

Integrated Uncertainty Management and Applications
Integrated Uncertainty Management and Applications

Author: Van-Nam Huynh

Publisher: Springer Science & Business Media

Published: 2010-03-26

Total Pages: 569

ISBN-13: 3642119603

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Solving practical problems often requires the integration of information and knowledge from many different sources, taking into account uncertainty and impreciseness. The 2010 International Symposium on Integrated Uncertainty Management and Applications (IUM’2010), which takes place at the Japan Advanced Institute of Science and Technology (JAIST), Ishikawa, Japan, between 9th–11th April, is therefore conceived as a forum for the discussion and exchange of research results, ideas for and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.

Uncertainty Management in Information Systems
Uncertainty Management in Information Systems

Author: Amihai Motro

Publisher: Springer Science & Business Media

Published: 1996-12-31

Total Pages: 490

ISBN-13: 9780792398035

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Uncertainty Management in Information Systems: From Needs to Solutions is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. The first part of this book describes issues and challenges in the area of imperfect information that confront information systems, and the second part covers the principal theories for modeling imperfect information, and shows how these theories may be adapted to information systems. All chapters are original contributions and present solutions that have been applied and the experiences that have been gained from those solutions. The material has been closely edited by the book's editors for content, consistency and style. This authoritative book is state-of-the-art coverage of `Uncertainty Management in Information Systems'.

Uncertainties in Modern Power Systems
Uncertainties in Modern Power Systems

Author: Ahmed F. Zobaa

Publisher: Academic Press

Published: 2020-10-26

Total Pages: 718

ISBN-13: 0128208937

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Uncertainties in Modern Power Systems combines several aspects of uncertainty management in power systems at the planning and operation stages within an integrated framework. This book provides the state-of-the-art in electric network planning, including time-scales, reliability, quality, optimal allocation of compensators and distributed generators, mathematical formulation, and search algorithms. The book introduces innovative research outcomes, programs, algorithms, and approaches that consolidate the present status and future opportunities and challenges of power systems. The book also offers a comprehensive description of the overall process in terms of understanding, creating, data gathering, and managing complex electrical engineering applications with uncertainties. This reference is useful for researchers, engineers, and operators in power distribution systems. - Includes innovative research outcomes, programs, algorithms, and approaches that consolidate current status and future of modern power systems - Discusses how uncertainties will impact on the performance of power systems - Offers solutions to significant challenges in power systems planning to achieve the best operational performance of the different electric power sectors

Scalable Uncertainty Management
Scalable Uncertainty Management

Author: Nahla Ben Amor

Publisher: Springer Nature

Published: 2019-12-02

Total Pages: 462

ISBN-13: 3030355144

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This book constitutes the refereed proceedings of the 13th International Conference on Scalable Uncertainty Management, SUM 2019, which was held in Compiègne, France, in December 2019. The 25 full, 4 short, 4 tutorial, 2 invited keynote papers presented in this volume were carefully reviewed and selected from 44 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models.

Scalable Uncertainty Management
Scalable Uncertainty Management

Author: Eyke Hüllermeier

Publisher: Springer

Published: 2012-09-11

Total Pages: 662

ISBN-13: 3642333621

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This book constitutes the refereed proceedings of the 6th International Conference on Scalable Uncertainty Management, SUM 2012, held in Marburg, Germany, in September 2012. The 41 revised full papers and 13 revised short papers were carefully reviewed and selected from 75 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.

Scalable Uncertainty Management
Scalable Uncertainty Management

Author: Lluis Godo

Publisher: Springer

Published: 2009-08-29

Total Pages: 318

ISBN-13: 3642043887

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This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.

Research Challenges in Modeling and Simulation for Engineering Complex Systems
Research Challenges in Modeling and Simulation for Engineering Complex Systems

Author: Richard Fujimoto

Publisher: Springer

Published: 2017-08-18

Total Pages: 138

ISBN-13: 3319585444

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This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.