Hybrid Intelligent Systems Based on Fuzzy Logic and Deep Learning

被引：5
|
作者：
Averkin, Alexey [1 ]
机构：
[1] RAS, Fed Res Ctr Informat & Comp Sci, Vavilova 42, Moscow, Russia
来源：
ARTIFICIAL INTELLIGENCE | 2019年 / 11866卷
关键词：
Deep learning; Neural networks; Rule extraction; Convolutional neural network; Machine learning; Artificial intelligence; NEURAL-NETWORKS; EXTRACTING RULES;
D O I：
10.1007/978-3-030-33274-7_1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The purpose of this lecture is to establish the fundamental links between two important areas of artificial intelligence - fuzzy logic and deep learning. This approach will allow researchers in the field of fuzzy logic to develop application systems in the field of strong artificial intelligence, which are also of interest to specialists in the field of machine learning. The lecture also examines how neuro-fuzzy networks make it possible to establish a link between symbolic and connectionist schools of artificial intelligence. A lot of methods of rule extraction from neural networks are also investigated.
引用
收藏
页码：3 / 12
页数：10
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