Deadline Date: 30 June 2026
In the real world, information is not always black-and-white and precise without a doubt. A great deal of human knowledge, perception and decision-making is built on "fuzziness". For instance, concepts such as "the temperature is very high", "the speed is very fast", and "this person is very young" have gradual and unclear boundaries. Traditional binary logic seems inadequate when dealing with this kind of information. Fuzzy information processing was born precisely to address this challenge. Its core theoretical basis is the theory of fuzzy sets. Unlike in classical set theory, where an element either completely belongs to or completely does not belong to a set, fuzzy sets describe the degree to which an element belongs to a certain set through a membership function, and this value varies continuously between 0 and 1. This enables us to quantify and manipulate these fuzzy concepts in mathematical language. The significance of fuzzy information processing lies in the effective modeling of uncertainties, serving as a bridge for human-computer interaction, enhancing the control and decision-making capabilities of complex systems, and promoting the development of intelligent computing.
This special issue of RIMNI aims to showcase the latest research progress, innovative methods, and cutting-edge applications in the field of fuzzy information processing. We hope to bring together the wisdom of researchers around the world to explore how to utilize fuzzy theory to solve increasingly complex decision-making, control, and data analysis problems in the real world. The special issue will focus on the integration of fuzzy theory with other advanced computing paradigms, as well as its unique value in addressing the challenges of big data, artificial intelligence, and complex systems.
This special issue welcomes high-quality original research or in-depth reviews covering theories, methods, algorithms, and applications. We encourage contributors to explore the boundaries of fuzzy information processing and apply it to emerging scientific and technological fields. The specific themes include, but are not limited to, the following topics:
New fuzzy sets and their extended theories
A new architecture of fuzzy logic and reasoning systems
Fuzzy information granulation and word computation
Fuzzy clustering and classification algorithms
Fuzzy regression analysis and prediction model
Fuzzy optimization and decision-making methods
Fuzzy feature selection and dimensionality reduction techniques
Fuzzy data mining and knowledge discovery
Fuzzy affective computing
Fuzzy image and video processing
Fuzzy neural networks and their deep learning variants
The integration of fuzzy systems with rough sets and evidence theory
Fuzzy reinforcement learning
Fuzzy product design
Interpretable artificial intelligence based on fuzzy rules
Editorial board
