Editorial: Applications of Fuzzy Systems in Data Science and Big Data

Abstract

The papers in this special section focus on applications of fuzzy systems in data science and Big Data. In the era of Big Data, intelligent as well as fuzzy tools have become very important to understanding our changing Internet-of-Things-driven data-centric world. Extracting “intelligence” from massive amounts of data has allowed us to support decision making processes in many fields, ranging from common fields like medicine and engineering to more lucrative industries such as vehicular technology and environmental stressors. In line with the shift in many industries to analyzing big data, has added in the fuzzy perspective to allow new ways of reasoning. Examples include interpretability of computing schemes, which have become more and more complex. Yet, successful applications of biomathematical modeling in a fuzzy environment have shown a good alternative to mere common black-box tools. In the call for papers of this special issue, we had devoted our interest in research pertaining to the current state-of-the-art research in the application of fuzzy systems regarding data science and big data analytics. We actively solicited recent results mainly concerned with recent advances and challenges in the theory and applications of fuzzy systems in the fields of data sciences and big data environments.