Synthesis and Learning of Fuzzy Neural Networks for Solving Forecasting Problems

被引：0
|
作者：
Okrenets, Serhii [1 ]
Fefelov, Andrii [1 ]
Lytvynenko, Volodymyr [1 ]
Sypenko, Volodymyr [2 ]
Korobchynskyi, Maksym [3 ]
Voronenko, Maria [1 ]
机构：
[1] Kherson Natl Tech Univ, 24 Beryslavske Highway, UA-73008 Kherson, Ukraine
[2] Natl Univ Life & Environm Sci, Kiev, Ukraine
[3] Mil Diplomat Acad, Kiev, Ukraine
来源：
PROCEEDINGS OF THE 2017 9TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS), VOL 2 | 2017年
关键词：
neuro-fuzzy networks; artificial immune network; fuzzy inference neural networks; forescating;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Two variations of the network are described i.e. Larsen model and Tsukamoto model. In each case an artificial immune network is proposed as a means of building fuzzy network structure and performing parameters inference.
引用
收藏
页码：1088 / 1093
页数：6
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