PyIT2FLS：一个开源Python框架，用于灵活和可扩展地开发类型1和区间类型2模糊逻辑模型

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-04-09 DOI:10.1016/j.softx.2025.102146

Amir Arslan Haghrah, Sehraneh Ghaemi, Mohammad Ali Badamchizadeh

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引用次数: 0

摘要

模糊集理论和模糊逻辑已经成为将专家知识转化为数学模型和从数值数据中提取有意义的见解的重要工具。尽管它们被广泛应用，但在Python中缺乏一个全面和集成的模糊逻辑开发工具。为了解决这个问题，我们开发了PyIT2FLS，这是一个用于创建Type-1和Interval Type-2模糊逻辑模型的开源框架。除了支持广泛的隶属函数、t-范数、s-范数和模糊运算符，并促进TSK和Mamdani系统的开发之外，PyIT2FLS与其他工具包的区别在于，它提供了优化算法的简单集成，例如元启发式技术，用于有效地调整模糊系统参数。这个全面的工具包弥合了模糊逻辑理论与实际应用之间的鸿沟，使新的智能方法和方案能够快速发展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.