Evolving fuzzy linear regression trees

A. Lemos, W. Caminhas, F. Gomide
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引用次数: 2

Abstract

This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared against alternative evolving fuzzy models and classic models with fixed structures. The results suggest that evolving fuzzy regression tree is a promising approach for adaptive system modeling.
进化模糊线性回归树
本文介绍了一种基于树形结构的进化模糊建模新方法。该系统是一个模糊线性回归树,其拓扑结构可以通过统计模型选择测试不断更新。模糊线性回归树是在每个叶子上都有线性模型的模糊树。在一个预测问题上评价了进化线性回归方法,并将其与备选进化模糊模型和经典固定结构模型进行了比较。结果表明,进化模糊回归树是一种很有前途的自适应系统建模方法。
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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