A Dynamic Hierarchical Genetic-Fuzzy Sugeno Network

被引：0
|
作者：
Macmann, Owen [1 ]
Cohen, Kelly [1 ]
机构：
[1] Univ Cincinnati, 2600 Clifton Ave, Cincinnati, OH 45221 USA
来源：
FUZZY INFORMATION PROCESSING 2020 | 2022年 / 1337卷
关键词：
SYSTEMS; MODEL;
D O I：
10.1007/978-3-030-81561-5_27
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A class of predictive algorithms that use genetic-fuzzy trees has risen to prominence in recent years. These algorithms are defined by three features: fuzzy logic, cascading decision trees, and genetic optimization. This paper presents an algorithm in this class that uses a cascading tree of Takagi-Sugeno systems, where the structure of the tree and the order of the elements within the tree are calculated procedurally by genetic algorithm. The resulting structure is unlike a tree and more akin to a honeycomb. This algorithm is shown herein to compare favorably with similar classes of predictive algorithms.
引用
收藏
页码：327 / 335
页数：9
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