Advances on Belief Functions and Their Applications

  in Special Issue   Posted on November 2, 2017

Information for the Special Issue

Special Issue Call for Papers:

The theory of belief functions, also known as evidence theory or Dempster-Shafer theory (DST), is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories. DST was first introduced by Arthur P. Dempster in 1960s, and was later developed by Glenn Shafer in 1970s. During the last fifty years, numerous approaches have been developed to improve the existing theory of belief functions and to extend its applications in various areas. A series of International conferences and schools on Belief Functions have been successfully held since 2010, and more and more sessions about belief functions are included in other related conferences. For example, there were seven sessions on belief functions at the 20th International Conference on Information Fusion in 2017 (FUSION 2017). There is a large and quickly expanding research community interested in the topics related with belief functions.

The objective of this special issue is to collect and report the recent advances on the theory and applications of belief functions. High quality contributions addressing related theoretical and/or practical aspects are expected.

The submissions can be revised and significantly extended versions of recent conference papers (with, e.g., additional results, detailed proofs, applications, etc.) related with belief functions, and this call for papers is also open to everyone interested in the topic of this special issue.

Topics include but are not limited to:


  • Decision making
  • Combination rules
  • Conditioning
  • Continuous belief functions
  • Independence and graphical models
  • Statistical inference
  • Geometry and distance metrics
  • Mathematical foundations
  • Computational frameworks
  • Links with other uncertainty theories


  • Data and information fusion
  • Pattern recognition
  • Machine learning and clustering
  • Tracking and data association
  • Data mining
  • Signal and image processing
  • Computer vision
  • Medical diagnosis
  • Business decision
  • Risk analysis
  • Engineering and environment
  • Climate change

Instructions for submission

All submissions should follow the “Guide for Authors” of IJAR journal while preparing your manuscript:

All submissions will undergo the standard review process of the journal. The submission website for IJAR journal is located at:

Authors must select the special issue BELIEF FUNCTIONS 2017 as the article type.

Important Dates:

31 Mar., 2018: Submission deadline

30 Jun., 2018: Notification of the first-round review

30 Nov., 2018: Final notice of acceptance/reject

Guest Editors:

Dr. Zhunga Liu (Northwestern Polytechnical University, Xian, China.)

Dr. Yong Deng (Southwest University, Chongqing, China)

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