Guest Editorial Special Issue on Emerging Computational Intelligence Techniques for Decision Making with Big Data in Uncertain Environments

Weiping Dingr, Nikhil R. Pal, Chin Teng Lin, Yiu Ming CHEUNG, Zehong Cao, Wenjian Luo

Research output: Contribution to journalEditorial

Abstract

The papers in this special section focus on emerging computational intelligent techniques for decision making with Big Data in uncertain environments. Decision making in a big-data environment poses many challenges because of the high dimensional, heterogeneous, complex, unstructured, and unpredictable characteristics of the data which often suffer from different kinds of uncertainty. The uncertainty in the data may arise due to many factors including missing values, imprecise measurements, changes in process characteristics during the data generation period, lack of appropriate monitoring of data measurement process to name a few. Internet-of-Things (IoT) systems usually generate a large amount of unstructured and heterogeneous data demanding specialized techniques for data analytics. Thus, decision making in such an environment poses significant challenges and often demands new and innovative design techniques and algorithms for decision making.
Original languageEnglish
Pages (from-to)2-5
Number of pages4
JournalIEEE Transactions on Emerging Topics in Computational Intelligence
Volume5
Issue number1
Early online date21 Jan 2021
DOIs
Publication statusPublished - Feb 2021

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computational Mathematics
  • Control and Optimization

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