Fully Scalable Fuzzy Neural Network for Data Processing

被引:0
作者
Apiecionek, Lukasz [1 ]
机构
[1] Kazimierz Wielki Univ Bydgoszcz, Fac Comp Sci, Jana Karola Chodkiewicza 30, Bydgoszcz, Poland
关键词
fuzzy logic; artificial neural network; Industry; 4.0; data processing; LEARNING ALGORITHM; ANFIS;
D O I
10.3390/s24165169
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The primary objective of the research presented in this article is to introduce an artificial neural network that demands less computational power than a conventional deep neural network. The development of this ANN was achieved through the application of Ordered Fuzzy Numbers (OFNs). In the context of Industry 4.0, there are numerous applications where this solution could be utilized for data processing. It allows the deployment of Artificial Intelligence at the network edge on small devices, eliminating the need to transfer large amounts of data to a cloud server for analysis. Such networks will be easier to implement in small-scale solutions, like those for the Internet of Things, in the future. This paper presents test results where a real system was monitored, and anomalies were detected and predicted.
引用
收藏
页数:14
相关论文
共 24 条
[1]   FUZZY NEURAL NETWORKS - A SURVEY [J].
BUCKLEY, JJ ;
HAYASHI, Y .
FUZZY SETS AND SYSTEMS, 1994, 66 (01) :1-13
[2]  
CHUNG FL, 1993, IEEE IJCNN, P2739
[3]   Coordinated control system modeling of ultra-supercritical unit based on a new fuzzy neural network [J].
Hou, Guolian ;
Xiong, Jian ;
Zhou, Guiping ;
Gong, Linjuan ;
Huang, Congzhi ;
Wang, Shunjiang .
ENERGY, 2021, 234
[4]   A LEARNING ALGORITHM OF FUZZY NEURAL NETWORKS WITH TRIANGULAR FUZZY WEIGHTS [J].
ISHIBUCHI, H ;
KWON, K ;
TANAKA, H .
FUZZY SETS AND SYSTEMS, 1995, 71 (03) :277-293
[5]   ANFIS - ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM [J].
JANG, JSR .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1993, 23 (03) :665-685
[6]  
LEE S C, 1975, Mathematical Biosciences, V23, P151, DOI 10.1016/0025-5564(75)90125-X
[7]   Design of an interval type-2 fuzzy neural network sliding mode robust controller for higher stability of magnetic spacecraft attitude control [J].
Liu, Xuan ;
Zhao, Taoyan ;
Cao, Jiangtao ;
Li, Ping .
ISA TRANSACTIONS, 2023, 137 :144-159
[8]   MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction [J].
Nasiri, Hamid ;
Ebadzadeh, Mohammad Mehdi .
NEUROCOMPUTING, 2022, 507 :292-310
[9]   Low-Rank Tensor Regularized Graph Fuzzy Learning for Multi-View Data Processing [J].
Pan, Baicheng ;
Li, Chuandong ;
Che, Hangjun ;
Leung, Man-Fai ;
Yu, Keping .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 70 (01) :2925-2938
[10]   Fixed/Preassigned-time synchronization of high-dimension-valued fuzzy neural networks with time-varying delays via nonseparation approach [J].
Pang, Mengzhen ;
Zhang, Ziye ;
Wang, Xianghua ;
Wang, Zhen ;
Lin, Chong .
KNOWLEDGE-BASED SYSTEMS, 2022, 255