基于统计数据的模糊逻辑包含系统设置算法

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-04-18 DOI:10.3103/S0005105523010028

M. S. Golosovskiy, A. V. Bogomolov, D. S. Tobin

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引用次数: 0

摘要

提出了一种基于统计数据的零阶Sugeno型模糊推理系统整定算法。该算法基于在参考点周围选择区域，找到所选区域的质心坐标，并利用它们建立模糊推理系统。证明了该算法的收敛性定理。本文给出了在改变输入变量隶属函数个数和统计数据点个数的条件下研究算法质量的结果，在此基础上对模糊推理系统进行了调整。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Algorithm for Setting Fuzzy Logical Inclusion Systems Based on Statistical Data

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Algorithm for Setting Fuzzy Logical Inclusion Systems Based on Statistical Data

An original algorithm for tuning zero-order Sugeno-type fuzzy inference systems based on statistical data is presented. The algorithm is based on selecting areas around the reference points, finding the coordinates of the center of mass of the selected areas, and using them to set up a fuzzy inference system. A convergence theorem is proven for the proposed algorithm. The paper presents the results of studying the quality of the algorithm under conditions of changing the number of membership functions of input variables and the number of statistical data points, on the basis of which the fuzzy inference systems were tuned.

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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.