Information, Uncertainty and Fusion

Information, Uncertainty and Fusion

Author: Bernadette Bouchon-Meunier

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 456

ISBN-13: 1461552095

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As we stand at the precipice of the twenty first century the ability to capture and transmit copious amounts of information is clearly a defining feature of the human race. In order to increase the value of this vast supply of information we must develop means for effectively processing it. Newly emerging disciplines such as Information Engineering and Soft Computing are being developed in order to provide the tools required. Conferences such as the International Conference on Information Processing and ManagementofUncertainty in Knowledge-based Systems (IPMU) are being held to provide forums in which researchers can discuss the latest developments. The recent IPMU conference held at La Sorbonne in Paris brought together some of the world's leading experts in uncertainty and information fusion. In this volume we have included a selection ofpapers from this conference. What should be clear from looking at this volume is the number of different ways that are available for representing uncertain information. This variety in representational frameworks is a manifestation of the different types of uncertainty that appear in the information available to the users. Perhaps, the representation with the longest history is probability theory. This representation is best at addressing the uncertainty associated with the occurrence of different values for similar variables. This uncertainty is often described as randomness. Rough sets can be seen as a type of uncertainty that can deal effectively with lack of specificity, it is a powerful tool for manipulating granular information.


Uncertainty Theories and Multisensor Data Fusion

Uncertainty Theories and Multisensor Data Fusion

Author: Alain Appriou

Publisher: John Wiley & Sons

Published: 2014-06-30

Total Pages: 0

ISBN-13: 1848213549

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Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessary? How can the available measurements be characterized in such a case? What is the purpose and the specificity of information fusion processing in multiple sensor systems? Considering the different uncertainty formalisms, a set of coherent operators corresponding to the different steps of a complete fusion process is then developed, in order to meet the requirements identified in the first part of the book.


Information Quality in Information Fusion and Decision Making

Information Quality in Information Fusion and Decision Making

Author: Éloi Bossé

Publisher: Springer

Published: 2019-04-02

Total Pages: 620

ISBN-13: 303003643X

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This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.


Uncertainty-sensitive Heterogeneous Information Fusion

Uncertainty-sensitive Heterogeneous Information Fusion

Author: Paul K. Davis

Publisher: Rand Corporation

Published: 2016

Total Pages: 0

ISBN-13:

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Presents research on methods for heterogeneous information fusion--combining data that are qualitative, subjective, fuzzy, ambiguous, contradictory, and even deceptive, in order to form a realistic assessment of threat in a counterterrorism context.


Combating Uncertainty With Fusion

Combating Uncertainty With Fusion

Author:

Publisher:

Published: 2003

Total Pages: 35

ISBN-13:

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This report is a summary of a NASA/ONR-sponsored workshop, Combating Uncertainty with Fusion, that was organized in Woods Hole in April 2002. The main purpose of the workshop was to address a class of difficult computational problems that are characterized by combining large amounts of data or datasets from diverse sources that are related in complex, stochastic, and poorly understood ways. The intent was to determine whether understanding of biological fusion processes could provide guidance to the development of robust algorithms that would alleviate the difficulties encountered in a variety of application areas including the Earth Observation System.


Hesitant Fuzzy and Probabilistic Information Fusion

Hesitant Fuzzy and Probabilistic Information Fusion

Author: Zhan Su

Publisher: Springer

Published: 2024-07-22

Total Pages: 0

ISBN-13: 9789819731398

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This book introduces the current research progress on hesitant fuzzy decision-making based on probability theory and methods. From the perspectives of theory expansion, information fusion, and information mining, it explores novel perspectives, ideas, and techniques for addressing hesitant fuzzy uncertain decision-making problems and demonstrates them through practical applications and case studies. It aims to provide a reference for researchers, practitioners, and graduate students in the fields of decision analysis, fuzzy theory, and information fusion.


Aggregation and Fusion of Imperfect Information

Aggregation and Fusion of Imperfect Information

Author: Bernadette Bouchon-Meunier

Publisher: Physica

Published: 2014-03-12

Total Pages: 278

ISBN-13: 9783662110720

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This book presents the main tools for aggregation of information given by several members of a group or expressed in multiple criteria, and for fusion of data provided by several sources. It focuses on the case where the availability knowledge is imperfect, which means that uncertainty and/or imprecision must be taken into account. The book contains both theoretical and applied studies of aggregation and fusion methods in the main frameworks: probability theory, evidence theory, fuzzy set and possibility theory. The latter is more developed because it allows to manage both imprecise and uncertain knowledge. Applications to decision-making, image processing, control and classification are described.