Possibility Theory for the Design of Information Fusion Systems. 1st ed. 2019

種類:

電子ブック

責任表示:

by Basel Solaiman, Éloi Bossé

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2019

著者名:

• Solaiman, Basel.
• Bossé, Éloi.
• SpringerLink (Online service)

シリーズ名:

Information Fusion and Data Science ;

ISBN:

9783030328535 [3030328538]    

注記:

Chapter1: Introduction to possibility theory -- Chapter2: Fundamental possibilistic concepts -- Chapter3: Joint Possibility Distributions and Conditioning -- Chapter4: Possibilistic Similarity Measures -- Chapter5: The interrelated uncertainty modeling theories -- Chapter6: Possibility integral -- Chapter7: Fusion operators and decision-making criteria in the framework of possibility theory -- Chapter8: Possibilistic concepts applied to soft pattern classification -- Chapter9: The use of possibility theory in the design of information fusion systems.
This practical guidebook describes the basic concepts, the mathematical developments, and the engineering methodologies for exploiting possibility theory for the computer-based design of an information fusion system where the goal is decision support for industries in smart ICT (information and communications technologies). This exploitation of possibility theory improves upon probability theory, complements Dempster-Shafer theory, and fills an important gap in this era of Big Data and Internet of Things. The book discusses fundamental possibilistic concepts: distribution, necessity measure, possibility measure, joint distribution, conditioning, distances, similarity measures, possibilistic decisions, fuzzy sets, fuzzy measures and integrals, and finally, the interrelated theories of uncertainty..uncertainty. These topics form an essential tour of the mathematical tools needed for the latter chapters of the book. These chapters present applications related to decision-making and pattern recognition schemes, a

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