Data-Driven Granular Computing Systems and Applications

摘要

Granular Computing (GrC), as a framework for data/information processing, is an umbrella term that encompasses a breadth of Soft Computing methods. Focusing on Machine Learning and Artificial Intelligence, we have experienced significant research growth in the direct use of data/information in order to computationally learn how systems behave, perform, evolve and in general capture information in the form of mathematical structures (models). Granular Computing has a significant role to play in the development of data-driven Machine Learning methods, in particular when human centricity is important. Desired traits include high levels of system interpretability, direct use of human expert knowledge, use of human-like information capture, as well as elicitation of linguistic-based rules.