Call for Submissions: Emerging Research on COVID-19

The Fuzzy Optimizaiton and Decision Making Editorial Office is launching a new effort of identifying some emerging research directions related to fuzzy optimization and decision making with individual associate editor(s) to call for timely submissions.

Facing the challenge of pandemic COVID-19, Professor Baoding Liu (AE) would like to invite submissions that employ/develop uncertainty theory for epidemic study. The following is his message:

Different from probabilistic statistics, uncertain statistics is a set of mathematical techniques for collecting, analyzing and interpreting data by uncertainty theory. Some topics of uncertain statistics include uncertain regression analysis, uncertain times series, uncertain differential equation, and uncertain hypothesis test. For analyzing and predicting the data of COVID-19 infections all over the world, uncertain statistics seems to do well. The papers related to uncertain statistics for epidemiological data analysis are welcome.

All submissions answering this call will go through the normal review process using the same evaluation standard, but with a higher priority to appear in FODM early.

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