State of Art in Fuzzy Logic

Abstract

Artificial intelligence and machine learning research has recently evolved, helping academic and industrial organizations. Fuzzy information processing is vital in data- and knowledge-intensive applications with high uncertainty. Fuzzy sets are used to improve database approaches for handling fuzzy data or accessing crunchy facts. This led to several scientific contributions. The present paper was analyzed and reviewed using bibliometric analysis with network analysis from January 2017 to July 2022. The study considered 80 chosen scientific publications for an in-depth literature review. The goal of this research is to look at, examine, and build a conceptual framework for future research on the present scientific discoveries on the use or progress of machine learning using fuzzy logic in a variety of disciplines such as Computer science, Engineering, Mathematics/Statistics, Medical, Finance, and Agriculture fields. Moreover, the study contrasts fuzzy querying with conventional data models. This survey study suggests prospective topics for further research in fuzzy data processing and provides a broad overview of the approaches for fuzzy predictive modeling and retrieval.