Fully Scalable Fuzzy Neural Network for Data Processing

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.

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Publication Details

Journal
Sensors
Published
2024-08-10
DOI
https://doi.org/10.3390/s24165169
Citations
8
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
2.78
Controls
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article

Fully Scalable Fuzzy Neural Network for Data Processing

Łukasz Apiecionek
8 citations
Sensors
Fuzzy Logic and Control Systems
2.78
article

Fully Scalable Fuzzy Neural Network for Data Processing

Łukasz Apiecionek
article en
8 citations

Abstract

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.

SensorsVol. 24(16)
Kazimierz Wielki University in Bydgoszcz (PL)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
Fuzzy Logic and Control Systems
2.78
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