This paper introduces \textsc{FuzzyLogic.jl}, a Julia library to perform fuzzy inference. The library is fully open-source and released under a permissive license. The core design principles of the library are: user-friendliness, flexibility, efficiency and interoperability. Particularly, our library is easy to use, allows to specify fuzzy systems in an expressive yet concise domain specific language, has several visualization tools, supports popular inference systems like Mamdani, Sugeno and Type-2 systems, can be easily expanded with custom user settings or algorithms and can perform fuzzy inference efficiently. It also allows reading fuzzy models from other formats such as Matlab .fis, FCL or FML. In this paper, we describe the library main features and benchmark it with a few examples, showing it achieves significant speedup compared to the Matlab fuzzy toolbox.

翻译：本文介绍了FuzzyLogic.jl，一个用于执行模糊推理的Julia库。该库完全开源，并在宽松许可下发布。库的核心设计原则是：用户友好性、灵活性、高效性和互操作性。特别地，我们的库易于使用，允许以富有表现力且简洁的领域特定语言指定模糊系统，提供多种可视化工具，支持流行的推理系统如Mamdani、Sugeno和Type-2系统，可轻松通过自定义用户设置或算法进行扩展，并能高效执行模糊推理。此外，它还支持从其他格式（如Matlab的.fis、FCL或FML）读取模糊模型。本文描述了该库的主要功能，并通过若干示例进行基准测试，表明与Matlab模糊工具箱相比，该库实现了显著的加速效果。