PyIT2FLS: An open-source Python framework for flexible and scalable development of type 1 and interval type 2 fuzzy logic models

Abstract

Fuzzy set theory and fuzzy logic have become essential tools for converting expert knowledge into mathematical models and extracting meaningful insights from numerical data. Despite their wide application, a comprehensive and integrated tool for fuzzy logic development in Python has been lacking. To address this gap, we developed PyIT2FLS, an open-source framework for creating both Type-1 and Interval Type-2 fuzzy logic models. In addition to supporting a broad range of membership functions, t-norms, s-norms, and fuzzy operators, and facilitating the development of TSK and Mamdani systems, PyIT2FLS distinguishes itself from other toolkits by offering an easy integration of optimization algorithms, such as meta-heuristic techniques, for efficiently tuning fuzzy system parameters. This comprehensive toolkit bridges the divide between fuzzy logic theory and practical applications, enabling the rapid development of novel intelligent methods and schemes.

Keywords

• Fuzzy logics
• Soft computing
• Computational intelligence
• Decision-making systems
• Open-source software
• Python